Create README.md

README.md

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+---
+base_model: Finnish-NLP/Ahma-7B
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+- trl
+license: apache-2.0
+language:
+- en
+- fi
+datasets:
+- mpasila/LumiOpenInstruct-GrypheSlimOrca-Mix
+- LumiOpen/instruction-collection-fin
+- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
+library_name: peft
+---
+So this is only the 500th step (out of 3922) trained on Google Colab because I'm a little low on money but at least that's free.. While testing the LoRA it seems to perform fairly well. The only real issue with this base model is that it only has 2048 token context size.
+
+The trained formatting should be ChatML but it seemed to work better with Mistral's formatting for some reason (could be just due to me not having merged the model yet).
+
+Dataset used was [a mix](https://huggingface.co/datasets/mpasila/LumiOpenInstruct-GrypheSlimOrca-Mix) of these:
+
+[LumiOpen/instruction-collection-fin](https://huggingface.co/datasets/LumiOpen/instruction-collection-fin)
+
+[Gryphe/Sonnet3.5-SlimOrcaDedupCleaned](https://huggingface.co/datasets/Gryphe/Sonnet3.5-SlimOrcaDedupCleaned)
+
+LoRA: [mpasila/Ahma-SlimInstruct-LoRA-V0.1-7B](https://huggingface.co/mpasila/Ahma-SlimInstruct-LoRA-V0.1-7B)
+
+# Uploaded Ahma-SlimInstruct-LoRA-V0.1-7B model
+
+- **Developed by:** mpasila
+- **License:** apache-2.0
+- **Finetuned from model :** Finnish-NLP/Ahma-7B
+
+This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)