Upload Gemma3ForConditionalGeneration
Browse files- README.md +199 -0
- config.json +59 -0
- generation_config.json +13 -0
- model-00001-of-00022.safetensors +3 -0
- model-00002-of-00022.safetensors +3 -0
- model-00003-of-00022.safetensors +3 -0
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- model-00006-of-00022.safetensors +3 -0
- model-00007-of-00022.safetensors +3 -0
- model-00008-of-00022.safetensors +3 -0
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- model-00010-of-00022.safetensors +3 -0
- model-00011-of-00022.safetensors +3 -0
- model-00012-of-00022.safetensors +3 -0
- model-00013-of-00022.safetensors +3 -0
- model-00014-of-00022.safetensors +3 -0
- model-00015-of-00022.safetensors +3 -0
- model-00016-of-00022.safetensors +3 -0
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- model-00018-of-00022.safetensors +3 -0
- model-00019-of-00022.safetensors +3 -0
- model-00020-of-00022.safetensors +3 -0
- model-00021-of-00022.safetensors +3 -0
- model-00022-of-00022.safetensors +3 -0
- model.safetensors.index.json +0 -0
README.md
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---
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library_name: transformers
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tags: []
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---
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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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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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [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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<!-- This should link to a Dataset Card if possible. -->
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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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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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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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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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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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[More Information Needed]
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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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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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config.json
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{
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"architectures": [
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"Gemma3ForConditionalGeneration"
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],
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"boi_token_index": 255999,
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| 6 |
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"eoi_token_index": 256000,
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| 7 |
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"eos_token_id": 1,
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"image_token_index": 262144,
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| 9 |
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"initializer_range": 0.02,
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| 10 |
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"mm_tokens_per_image": 256,
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| 11 |
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"model_type": "gemma3",
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| 12 |
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"text_config": {
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| 13 |
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"attention_bias": false,
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"attention_dropout": 0.0,
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| 15 |
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"attn_logit_softcapping": null,
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"cache_implementation": "hybrid",
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"final_logit_softcapping": null,
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"head_dim": 128,
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"hidden_activation": "gelu_pytorch_tanh",
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"hidden_size": 5376,
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| 21 |
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"initializer_range": 0.02,
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| 22 |
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"intermediate_size": 21504,
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"max_position_embeddings": 131072,
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"model_type": "gemma3_text",
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"num_attention_heads": 32,
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"num_hidden_layers": 62,
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"num_key_value_heads": 16,
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"query_pre_attn_scalar": 168,
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| 29 |
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"rms_norm_eps": 1e-06,
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"rope_local_base_freq": 10000.0,
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"rope_scaling": {
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"factor": 8.0,
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| 33 |
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"rope_type": "linear"
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},
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"rope_theta": 1000000.0,
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| 36 |
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"sliding_window": 1024,
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| 37 |
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"sliding_window_pattern": 6,
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| 38 |
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"torch_dtype": "float32",
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| 39 |
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"use_cache": false,
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| 40 |
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"vocab_size": 262208
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},
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"torch_dtype": "float32",
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| 43 |
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"transformers_version": "4.51.3",
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| 44 |
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"vision_config": {
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| 45 |
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"attention_dropout": 0.0,
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| 46 |
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"hidden_act": "gelu_pytorch_tanh",
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| 47 |
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"hidden_size": 1152,
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| 48 |
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"image_size": 896,
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| 49 |
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"intermediate_size": 4304,
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"layer_norm_eps": 1e-06,
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"model_type": "siglip_vision_model",
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"num_attention_heads": 16,
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"num_channels": 3,
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"num_hidden_layers": 27,
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"patch_size": 14,
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"torch_dtype": "float32",
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"vision_use_head": false
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}
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}
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generation_config.json
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{
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"do_sample": true,
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"eos_token_id": [
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1,
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106
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],
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"pad_token_id": 0,
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"top_k": 64,
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"top_p": 0.95,
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"transformers_version": "4.51.3"
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}
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model-00001-of-00022.safetensors
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