v-guidongnan
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Browse files- README.md +29 -185
- adapter_config.json +4 -4
- adapter_model.safetensors +2 -2
- added_tokens.json +25 -0
- config.json +53 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +45 -0
- tokenizer_config.json +240 -0
- vocab.json +0 -0
README.md
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tags:
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---
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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#### Hardware
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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license: apache-2.0
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tags:
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- trl
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- ppo
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- transformers
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- reinforcement-learning
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# TRL Model
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This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
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guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
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## Usage
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To use this model for inference, first install the TRL library:
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```bash
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python -m pip install trl
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```
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You can then generate text as follows:
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```python
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from transformers import pipeline
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generator = pipeline("text-generation", model="tzwilliam0/logs_morlhf/maxmin-dpo-init-kl-coef-0.1-rebuttal/batch_16")
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outputs = generator("Hello, my llama is cute")
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```
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If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
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```python
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from transformers import AutoTokenizer
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from trl import AutoModelForCausalLMWithValueHead
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tokenizer = AutoTokenizer.from_pretrained("tzwilliam0/logs_morlhf/maxmin-dpo-init-kl-coef-0.1-rebuttal/batch_16")
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model = AutoModelForCausalLMWithValueHead.from_pretrained("tzwilliam0/logs_morlhf/maxmin-dpo-init-kl-coef-0.1-rebuttal/batch_16")
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inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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outputs = model(**inputs, labels=inputs["input_ids"])
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```
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adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"up_proj",
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"k_proj",
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"
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"down_proj",
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"v_proj",
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"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"o_proj",
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"down_proj",
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"up_proj",
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"gate_proj",
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"v_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:6fd7a5e49ef1499a9a97e3880e304d80c72e5b5bdc39c0255c48092121742be5
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size 2497299608
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added_tokens.json
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{
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"</tool_call>": 151658,
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"<tool_call>": 151657,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652,
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"[PAD]": 151665
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}
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config.json
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{
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"accelerator_kwargs": {},
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"adap_kl_ctrl": false,
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"backward_batch_size": 5,
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"batch_size": 60,
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"cliprange": 0.2,
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"cliprange_value": 0.2,
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"compare_steps": 1,
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"early_stopping": true,
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"exp_name": "morlhf",
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"forward_batch_size": null,
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"gamma": 1,
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"global_backward_batch_size": 20,
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"global_batch_size": 240,
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"gradient_accumulation_steps": 5,
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"horizon": 10000,
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"init_kl_coef": 0.1,
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"is_encoder_decoder": false,
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"is_peft_model": true,
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"kl_penalty": "kl",
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"lam": 0.95,
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"learning_rate": 1e-05,
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"log_with": "wandb",
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"max_grad_norm": 0.5,
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"mini_batch_size": 1,
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"model_name": "unsloth/Qwen2.5-7B",
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"optimize_cuda_cache": true,
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"optimize_device_cache": false,
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"ppo_epochs": 4,
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"project_kwargs": {},
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"push_to_hub_if_best_kwargs": {},
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"query_dataset": "imdb",
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"ratio_threshold": 10.0,
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"remove_unused_columns": true,
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"reward_model": "sentiment-analysis:lvwerra/distilbert-imdb",
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"score_clip": null,
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"seed": 0,
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"steps": 20000,
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"target": 3,
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"target_kl": 1,
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"task_name": null,
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"tracker_kwargs": {
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"wandb": {
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"name": "maxmin-dpo-init-kl-coef-0.1-rebuttal"
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}
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},
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"tracker_project_name": "morlhf",
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"use_score_norm": false,
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"use_score_scaling": false,
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"vf_coef": 0.1,
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"whiten_rewards": false,
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"world_size": 4
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}
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merges.txt
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See raw diff
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b9ed27c4e1d335d31f6620e5971ae233d0ab4f43ace8ec1644b222da1f1fee8c
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size 15868
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special_tokens_map.json
ADDED
@@ -0,0 +1,45 @@
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{
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"additional_special_tokens": [
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"<|im_start|>",
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"<|im_end|>",
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"<|object_ref_start|>",
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"<|object_ref_end|>",
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"<|box_start|>",
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"<|box_end|>",
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"<|quad_start|>",
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"<|quad_end|>",
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"<|vision_start|>",
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"<|vision_end|>",
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"<|vision_pad|>",
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"<|image_pad|>",
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"<|video_pad|>"
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],
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"bos_token": {
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"content": "<s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer_config.json
ADDED
@@ -0,0 +1,240 @@
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1 |
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{
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2 |
+
"add_bos_token": false,
|
3 |
+
"add_prefix_space": false,
|
4 |
+
"added_tokens_decoder": {
|
5 |
+
"128244": {
|
6 |
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"content": "<unk>",
|
7 |
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"lstrip": false,
|
8 |
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"normalized": false,
|
9 |
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"rstrip": false,
|
10 |
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"single_word": false,
|
11 |
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"special": true
|
12 |
+
},
|
13 |
+
"128245": {
|
14 |
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"content": "<s>",
|
15 |
+
"lstrip": false,
|
16 |
+
"normalized": false,
|
17 |
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"rstrip": false,
|
18 |
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"single_word": false,
|
19 |
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"special": true
|
20 |
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},
|
21 |
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"128247": {
|
22 |
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"content": "</s>",
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23 |
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"lstrip": false,
|
24 |
+
"normalized": false,
|
25 |
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"rstrip": false,
|
26 |
+
"single_word": false,
|
27 |
+
"special": true
|
28 |
+
},
|
29 |
+
"151643": {
|
30 |
+
"content": "<|endoftext|>",
|
31 |
+
"lstrip": false,
|
32 |
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"normalized": false,
|
33 |
+
"rstrip": false,
|
34 |
+
"single_word": false,
|
35 |
+
"special": true
|
36 |
+
},
|
37 |
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"151644": {
|
38 |
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"content": "<|im_start|>",
|
39 |
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"lstrip": false,
|
40 |
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"normalized": false,
|
41 |
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"rstrip": false,
|
42 |
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"single_word": false,
|
43 |
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"special": true
|
44 |
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},
|
45 |
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"151645": {
|
46 |
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"content": "<|im_end|>",
|
47 |
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"lstrip": false,
|
48 |
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"normalized": false,
|
49 |
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"rstrip": false,
|
50 |
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"single_word": false,
|
51 |
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"special": true
|
52 |
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},
|
53 |
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"151646": {
|
54 |
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"content": "<|object_ref_start|>",
|
55 |
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"lstrip": false,
|
56 |
+
"normalized": false,
|
57 |
+
"rstrip": false,
|
58 |
+
"single_word": false,
|
59 |
+
"special": true
|
60 |
+
},
|
61 |
+
"151647": {
|
62 |
+
"content": "<|object_ref_end|>",
|
63 |
+
"lstrip": false,
|
64 |
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"normalized": false,
|
65 |
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"rstrip": false,
|
66 |
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"single_word": false,
|
67 |
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"special": true
|
68 |
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},
|
69 |
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"151648": {
|
70 |
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"content": "<|box_start|>",
|
71 |
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"lstrip": false,
|
72 |
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"normalized": false,
|
73 |
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"rstrip": false,
|
74 |
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"single_word": false,
|
75 |
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"special": true
|
76 |
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},
|
77 |
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"151649": {
|
78 |
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"content": "<|box_end|>",
|
79 |
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"lstrip": false,
|
80 |
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"normalized": false,
|
81 |
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"rstrip": false,
|
82 |
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"single_word": false,
|
83 |
+
"special": true
|
84 |
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},
|
85 |
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"151650": {
|
86 |
+
"content": "<|quad_start|>",
|
87 |
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"lstrip": false,
|
88 |
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"normalized": false,
|
89 |
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"rstrip": false,
|
90 |
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"single_word": false,
|
91 |
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"special": true
|
92 |
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},
|
93 |
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"151651": {
|
94 |
+
"content": "<|quad_end|>",
|
95 |
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"lstrip": false,
|
96 |
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"normalized": false,
|
97 |
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"rstrip": false,
|
98 |
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"single_word": false,
|
99 |
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"special": true
|
100 |
+
},
|
101 |
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"151652": {
|
102 |
+
"content": "<|vision_start|>",
|
103 |
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"lstrip": false,
|
104 |
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"normalized": false,
|
105 |
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"rstrip": false,
|
106 |
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"single_word": false,
|
107 |
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"special": true
|
108 |
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},
|
109 |
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"151653": {
|
110 |
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"content": "<|vision_end|>",
|
111 |
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"lstrip": false,
|
112 |
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"normalized": false,
|
113 |
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"rstrip": false,
|
114 |
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"single_word": false,
|
115 |
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"special": true
|
116 |
+
},
|
117 |
+
"151654": {
|
118 |
+
"content": "<|vision_pad|>",
|
119 |
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"lstrip": false,
|
120 |
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"normalized": false,
|
121 |
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"rstrip": false,
|
122 |
+
"single_word": false,
|
123 |
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"special": true
|
124 |
+
},
|
125 |
+
"151655": {
|
126 |
+
"content": "<|image_pad|>",
|
127 |
+
"lstrip": false,
|
128 |
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"normalized": false,
|
129 |
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"rstrip": false,
|
130 |
+
"single_word": false,
|
131 |
+
"special": true
|
132 |
+
},
|
133 |
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"151656": {
|
134 |
+
"content": "<|video_pad|>",
|
135 |
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"lstrip": false,
|
136 |
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"normalized": false,
|
137 |
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"rstrip": false,
|
138 |
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"single_word": false,
|
139 |
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"special": true
|
140 |
+
},
|
141 |
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"151657": {
|
142 |
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"content": "<tool_call>",
|
143 |
+
"lstrip": false,
|
144 |
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"normalized": false,
|
145 |
+
"rstrip": false,
|
146 |
+
"single_word": false,
|
147 |
+
"special": false
|
148 |
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},
|
149 |
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"151658": {
|
150 |
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"content": "</tool_call>",
|
151 |
+
"lstrip": false,
|
152 |
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"normalized": false,
|
153 |
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"rstrip": false,
|
154 |
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"single_word": false,
|
155 |
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"special": false
|
156 |
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},
|
157 |
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"151659": {
|
158 |
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"content": "<|fim_prefix|>",
|
159 |
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"lstrip": false,
|
160 |
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"normalized": false,
|
161 |
+
"rstrip": false,
|
162 |
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"single_word": false,
|
163 |
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"special": false
|
164 |
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},
|
165 |
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"151660": {
|
166 |
+
"content": "<|fim_middle|>",
|
167 |
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"lstrip": false,
|
168 |
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"normalized": false,
|
169 |
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"rstrip": false,
|
170 |
+
"single_word": false,
|
171 |
+
"special": false
|
172 |
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},
|
173 |
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"151661": {
|
174 |
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"content": "<|fim_suffix|>",
|
175 |
+
"lstrip": false,
|
176 |
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"normalized": false,
|
177 |
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"rstrip": false,
|
178 |
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"single_word": false,
|
179 |
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"special": false
|
180 |
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},
|
181 |
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"151662": {
|
182 |
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"content": "<|fim_pad|>",
|
183 |
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"lstrip": false,
|
184 |
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"normalized": false,
|
185 |
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"rstrip": false,
|
186 |
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"single_word": false,
|
187 |
+
"special": false
|
188 |
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},
|
189 |
+
"151663": {
|
190 |
+
"content": "<|repo_name|>",
|
191 |
+
"lstrip": false,
|
192 |
+
"normalized": false,
|
193 |
+
"rstrip": false,
|
194 |
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"single_word": false,
|
195 |
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"special": false
|
196 |
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},
|
197 |
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"151664": {
|
198 |
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"content": "<|file_sep|>",
|
199 |
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"lstrip": false,
|
200 |
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"normalized": false,
|
201 |
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"rstrip": false,
|
202 |
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"single_word": false,
|
203 |
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"special": false
|
204 |
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},
|
205 |
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"151665": {
|
206 |
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"content": "[PAD]",
|
207 |
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"lstrip": false,
|
208 |
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"normalized": false,
|
209 |
+
"rstrip": false,
|
210 |
+
"single_word": false,
|
211 |
+
"special": true
|
212 |
+
}
|
213 |
+
},
|
214 |
+
"additional_special_tokens": [
|
215 |
+
"<|im_start|>",
|
216 |
+
"<|im_end|>",
|
217 |
+
"<|object_ref_start|>",
|
218 |
+
"<|object_ref_end|>",
|
219 |
+
"<|box_start|>",
|
220 |
+
"<|box_end|>",
|
221 |
+
"<|quad_start|>",
|
222 |
+
"<|quad_end|>",
|
223 |
+
"<|vision_start|>",
|
224 |
+
"<|vision_end|>",
|
225 |
+
"<|vision_pad|>",
|
226 |
+
"<|image_pad|>",
|
227 |
+
"<|video_pad|>"
|
228 |
+
],
|
229 |
+
"bos_token": "<s>",
|
230 |
+
"clean_up_tokenization_spaces": false,
|
231 |
+
"eos_token": "</s>",
|
232 |
+
"errors": "replace",
|
233 |
+
"extra_special_tokens": {},
|
234 |
+
"model_max_length": 131072,
|
235 |
+
"pad_token": "[PAD]",
|
236 |
+
"padding_side": "left",
|
237 |
+
"split_special_tokens": false,
|
238 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
239 |
+
"unk_token": "<unk>"
|
240 |
+
}
|
vocab.json
ADDED
The diff for this file is too large to render.
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