Create README.md

README.md

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+---
+license: apache-2.0
+datasets:
+- BAAI/COIG-PC
+language:
+- zh
+library_name: transformers
+pipeline_tag: question-answering
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This is an experimental product that can be used to create new LLM bassed on Chinese language. It has been generated using [Chinese-LLaMA-Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca)
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+- **Developed by:** yjf9966
+- **Model type:** LLaMA with enhanced tokenizer-size-49964
+- **Language(s) (NLP):** Chinese
+- **License:** Apache 2.0
+- **Finetuned from model:** [Chinese-LLaMA-Alpaca](https://github.com/ymcui/Chinese-LLaMA-Alpaca)
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** https://huggingface.co/BlueWhaleX/Chinese-Alpaca-COIG-49954-13B-HF
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+You can use the raw model for next sentence prediction, but it's mostly intended to be fine-tuned on a downstream task.
+Note that this model is primarily aimed at being fine-tuned on tasks that use the whole sentence (potentially masked) to make decisions, such as sequence classification, token classification or question answering.
+
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+Even if the training data used for this model could be characterized as fairly neutral, this model can have biased predictions.
+It also inherits some of the bias of its dataset model.
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```
+import torch
+import transformers
+from transformers import LlamaTokenizer, LlamaForCausalLM
+
+def generate_prompt(text):
+    return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n" +
+               ### Instruction:\n\n{text}\n\n### Response:\n\n"""
+
+tokenizer = LlamaTokenizer.from_pretrained('BlueWhaleX/Chinese-Alpaca-COIG-49954-13B-HF')
+model = LlamaForCausalLM.from_pretrained('BlueWhaleX/Chinese-Alpaca-COIG-49954-13B-HF').half().cuda()
+model.eval()
+
+text = '王国维说：“自周之衰，文王、周公势力之瓦解也，国民之智力成熟于内，政治之纷乱乘之于外，上无统一之制度，下迫于社会之要求，于是诸于九流各创其学说。” 他意在说明 A. 分封制的崩溃 B. 商鞅变法的作用 C. 兼并战争的后果 D. 百家争鸣的原因'
+prompt = generate_prompt(text)
+input_ids = tokenizer.encode(prompt, return_tensors='pt').to('cuda')
+
+with torch.no_grad():
+    output_ids = model.generate(
+        input_ids=input_ids,
+        max_new_tokens=400,
+        temperature=0.2,
+        top_k=40,
+        top_p=0.9,
+        repetition_penalty=1.3
+    ).cuda()
+output = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+response = output.split("### Response:")[1].strip() 
+print("Response: ", response, '\n')
+```
+
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Data 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. -->
+
+BAAI/COIG-PC
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+80% for train dataset and 20% for test dataset
+
+
+#### Training Hyperparameters
+
+- **Training regime:** fp16 mixed precision, lr=1e-4, lora_rank=8, lora_alpha=32 <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+
+## Evaluation
+
+#### Testing Data
+
+<!-- This should link to a Data Card if possible. -->
+20% of the BAAI/COIG-PC dataset.
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+```
+@software{Chinese-Alpaca-COIG-49954-13B-HF,
+      title={An Enchanced Chinese Language Model based on the Chinese-Alpaca}, 
+      url={https://huggingface.co/BlueWhaleX/Chinese-Alpaca-COIG-49954-13B-HF},
+      year={2023}
+}
+```