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Cleanup readme

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Also added link for ExLlamaV2 quants if you don't mind

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  1. README.md +9 -12
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  ---
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  license: apache-2.0
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  base_model: mistralai/Mistral-7B-v0.1
 
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  tags:
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  - generated_from_trainer
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  model-index:
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  </details><br>
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- # out
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- This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
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- ## Model description
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- More information needed
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- ## Intended uses & limitations
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- More information needed
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- ## Training and evaluation data
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- More information needed
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  ## Training procedure
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  - lr_scheduler_warmup_steps: 10
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  - training_steps: 1602
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- ### Training results
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  ### Framework versions
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  - Transformers 4.38.0.dev0
 
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  ---
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  license: apache-2.0
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  base_model: mistralai/Mistral-7B-v0.1
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+ datasets: NeuralNovel/Neural-DPO
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  tags:
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  - generated_from_trainer
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  model-index:
 
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  </details><br>
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+ Creator: <a href="https://huggingface.co/NovoCode">NovoCode</a>
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+ Community Organization: <a href="https://huggingface.co/ConvexAI">ConvexAI</a>
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+ Discord: <a href="https://discord.gg/rJXGjmxqzS">Join us on Discord</a>
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+ ## Model description
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on [Neural-DPO](https://huggingface.co/datasets/NeuralNovel/Neural-DPO).
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+ This model should excel at question answering across a rich array of subjects across a wide range of domains such as literature, scientific research, and theoretical inquiries.
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+ ## ExLlamaV2 Quants
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+ ExLlamaV2 quants are available from [bartowski here](https://huggingface.co/bartowski/Mistral-NeuralDPO-v0.5-exl2)
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  ## Training procedure
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  - lr_scheduler_warmup_steps: 10
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  - training_steps: 1602
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  ### Framework versions
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  - Transformers 4.38.0.dev0