初始化项目，由ModelHub XC社区提供模型

Model: QwenCollection/Hercules-Mini-1.8B
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: other
+datasets:
+- Locutusque/hercules-v4.0
+language:
+- en
+inference:
+  parameters:
+    do_sample: true
+    temperature: 1
+    top_p: 0.7
+    top_k: 4
+    max_new_tokens: 250
+    repetition_penalty: 1.1
+---
+
+# Hercules-Mini-1.8B 
+
+<!-- Provide a quick summary of what the model is/does. -->
+We fine-tuned Qwen1.5-1.8B on Locutusque's Hercules-v4.
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This model has capabilities in math, coding, function calling, roleplay, and more. We fine-tuned it using 700,000 examples of Hercules-v4. 
+
+- **Developed by:** M4-ai
+- **Language(s) (NLP):** English and maybe Chinese
+- **License:** tongyi-qianwen license
+- **Finetuned from model:** [Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B)
+
+## 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. -->
+
+General purpose assistant, question answering, chain-of-thought, etc..
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+The eos token was not setup properly, so to prevent infinite generation you'll need to implement a stopping criteria when the model generates the <|im_end|> token. 
+
+### 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.
+
+## Evaluation
+Coming soon
+
+
+## Training Details
+
+### Training Data
+
+<!-- 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. -->
+https://huggingface.co/datasets/Locutusque/hercules-v4.0
+
+
+#### Training Hyperparameters
+
+- **Training regime:** bf16 non-mixed precision
+## Technical Specifications
+
+#### Hardware
+
+We used 8 Kaggle TPUs, and we trained at a global batch size of 256 and sequence length of 1536
+
+## Contributions
+
+Thanks to @Tonic, @aloobun, @fhai50032, and @Locutusque for their contributions to this model.