Update README.md

README.md

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-inference: false
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+apples ferret model 13b merged ready to go 
 
-**NOTE: New version available**  
-Please check out a newer version of the weights [here](https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md).
 
-<br>
-
-# Vicuna Model Card
-
-## Model Details
-
-Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
-
-- **Developed by:** [LMSYS](https://lmsys.org/)
-- **Model type:** An auto-regressive language model based on the transformer architecture.
-- **License:** Non-commercial license
-- **Finetuned from model:** [LLaMA](https://arxiv.org/abs/2302.13971).
-
-### Model Sources
-
-- **Repository:** https://github.com/lm-sys/FastChat
-- **Blog:** https://lmsys.org/blog/2023-03-30-vicuna/
-- **Paper:** https://arxiv.org/abs/2306.05685
-- **Demo:** https://chat.lmsys.org/
-
-## Uses
-
-The primary use of Vicuna is research on large language models and chatbots.
-The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.
-
-## How to Get Started with the Model
-
-- Command line interface: https://github.com/lm-sys/FastChat#vicuna-weights.  
-- APIs (OpenAI API, Huggingface API): https://github.com/lm-sys/FastChat/tree/main#api.  
-
-## Training Details
-
-Vicuna v1.3 is fine-tuned from LLaMA with supervised instruction fine-tuning.
-The training data is around 125K conversations collected from ShareGPT.com.
-See more details in the "Training Details of Vicuna Models" section in the appendix of this [paper](https://arxiv.org/pdf/2306.05685.pdf).
-
-## Evaluation
-
-Vicuna is evaluated with standard benchmarks, human preference, and LLM-as-a-judge. See more details in this [paper](https://arxiv.org/pdf/2306.05685.pdf) and [leaderboard](https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard).
-
-## Difference between different versions of Vicuna
-See [vicuna_weights_version.md](https://github.com/lm-sys/FastChat/blob/main/docs/vicuna_weights_version.md)
+informations on how to run at 
+https://github.com/apple/ml-ferret/tree/main