Create README.md

README.md

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+---
+license: apache-2.0
+inference: false
+datasets:
+- PengQu/langchain-MRKL-finetune
+- fnlp/moss-003-sft-data
+- anon8231489123/ShareGPT_Vicuna_unfiltered
+---
+
+
+**NOTE: This "delta model" cannot be used directly.**  
+Users have to apply it on top of the original LLaMA weights to get actual Vicuna weights.  
+See https://github.com/pengqu123/vicuna-13b-delta-finetuned-langchain-MRKL for instructions.
+<br>
+<br>
+
+# vicuna-13b-finetuned-langchain-MRKL
+
+## Model details
+
+**Model type:**
+vicuna-13b-finetuned-langchain-MRKL is an open-source chatbot trained by fine-tuning vicuna-13b on 15 examples with langchain-MRKL format.
+
+**Where to send questions or comments about the model:**
+https://github.com/pengqu123/vicuna-13b-delta-finetuned-langchain-MRKL/issues
+
+## Intended use
+**Primary intended uses:**
+The primary use of Vicuna is research on large language models and chatbots.
+
+**Primary intended users:**
+The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
+
+## Training dataset
+train only one epoch on mix data (sharegpt + 32*my.json + moss-003-sft-data)
+
+## Evaluation
+demo code: https://github.com/pengqu123/vicuna-13b-delta-finetuned-langchain-MRKL/blob/main/demo.ipynb
+No evaluation set. Because we don't improve the ability of model. we just make model fit langchain-MRKL strictly.
+We just want to show vicuna-13b's powerful ability about thinking and action.
+This is the first step. We hope if we get more samples about more tools, we can support more complicate plugins too.
+
+## Major Improvement
+- support langchain-MRKL(agent= "zero-shot-react-description")
+- very fast because of stritcly format(it doesn't generate redundant tokens)