Create README.md

README.md

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+---
+license: apache-2.0
+language:
+  - en
+  - fr
+  - de
+  - es
+  - it
+  - pt
+  - ru
+  - zh
+  - ja
+pipeline_tag: text-generation
+tags:
+- chat
+---
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6491e00e057b0928b3e07b75/DImxlQFoc56eiM_XgHDNk.png)
+This is the sixth in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. This model is fine-tuned on top of [Mistral-Large-Instruct-2407](https://huggingface.co/mistralai/Mistral-Large-Instruct-2407).
+
+## Prompting
+Model has been Instruct tuned with the Mistral formatting. A typical input would look like this:
+
+```py
+"""[INST] Hi there! [/INST]Nice to meet you!</s>[INST] Can I ask a question? [/INST]
+"""
+```
+
+## Credits
+- Stheno dataset (filtered)
+- [anthracite-org/kalo-opus-instruct-22k-no-refusal](anthracite-org/kalo-opus-instruct-22k-no-refusal)
+- [anthracite-org/nopm_claude_writing_fixed](https://huggingface.co/datasets/anthracite-org/nopm_claude_writing_fixed)
+
+This model has been a team effort, and the credits goes to all members of Anthracite.
+
+## Training
+The training was done for 1.5 epochs. We used 8x [AMD Instinct™ MI300X Accelerators](https://www.amd.com/en/products/accelerators/instinct/mi300/mi300x.html) for the full-parameter fine-tuning of the model.
+
+In addition to this, we noticed that Mistral Large models seemed much more sensitive to learning rate adjustments than other models:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6491e00e057b0928b3e07b75/xCK3ISKF6pWcMyO7MEzTA.png)
+
+We hypothesize this is primarily due to the particularly narrow and low variance weight distributions typical of Mistral derived models regardless of their scale.
+In the end, we settled on 2e-6 with an effective batch size of 64 (and a packed tokens batch size of 8192; this effectively ~500,000 tokens per batch).
+
+We also trained with a weight decay of 0.01 to help further stabilize the loss trajectory and mitigate overfitting.
+
+[<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)
+
+## Safety
+...