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README.md

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+---
+license: mit
+---
+
+# SciPhi-SearchAgent-Alpha-7B Model Card
+
+The SciPhi-SearchAgent-Alpha-7B is a Large Language Model (LLM) fine-tuned from Mistral-7B-v0.1. This model underwent a fine-tuning process using retrieval-augmented generation (RAG) over search with a fully synthetic dataset. The objective of this work is to generate accurate and well-cited summaries from a range of search results, providing more accurate answers to user queries. For best results, follow the prompting guidelines below.
+
+SciPhi-AI is available via a free hosted API, though the exposed model can vary. Currently, SciPhi-SearchAgent-Alpha-7B is available. More details can be found in the docs [here](https://sciphi.readthedocs.io/en/latest/setup/quickstart.html).
+
+## Model Architecture
+
+Base Model: Mistral-7B-v0.1
+
+**Architecture Features:**
+- Transformer-based model
+- Grouped-Query Attention
+- Sliding-Window Attention
+- Byte-fallback BPE tokenizer
+
+
+## Using the Model
+
+It is recommended to use a single search query. The model will return an answer using search results as context. 
+
+In order to use the model, you can go to the website https://search.sciphi.ai/, or you can run it locally using the following simple command:
+
+```
+export SCIPHI_API_KEY=MY_SCIPHI_API_KEY
+# Use the SciPhi `SearchAgent` for LLM RAG w/ AgentSearch
+python -m agent_search.scripts.run_rag run --query="What is Fermat's last theorem?"
+```
+
+See the documentation, linked above, for more information.
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+
+## References
+
+1. Lian, W., Goodson, B., Wang, G., Pentland, E., Cook, A., Vong, C., & Teknium. (2023). MistralOrca: Mistral-7B Model Instruct-tuned on Filtered OpenOrcaV1 GPT-4 Dataset. *HuggingFace repository*. [Link](https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca)
+2. Mukherjee, S., Mitra, A., Jawahar, G., Agarwal, S., Palangi, H., & Awadallah, A. (2023). Orca: Progressive Learning from Complex Explanation Traces of GPT-4. *arXiv preprint arXiv:2306.02707*.
+3. Longpre, S., Hou, L., Vu, T., Webson, A., Chung, H. W., Tay, Y., Zhou, D., Le, Q. V., Zoph, B., Wei, J., & Roberts, A. (2023). The Flan Collection: Designing Data and Methods for Effective Instruction Tuning. *arXiv preprint arXiv:2301.13688*.
+4. Mistral AI. (2023). Model Card for Mistral-7B-v0.1. The Mistral-7B-v0.1 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters. Mistral-7B-v0.1 outperforms Llama 2 13B on all benchmarks tested. For full details, please refer to the paper and release blog post. Model Architecture: Transformer with Grouped-Query Attention, Sliding-Window Attention, and Byte-fallback BPE tokenizer. [Link](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+
+
+## Acknowledgements
+
+Thank you to the [AI Alignment Lab](https://huggingface.co/Alignment-Lab-AI), [vikp](https://huggingface.co/vikp), [jph00](https://huggingface.co/jph00) and others who contributed to this work.