Instructions to use raulgdp/Ministral-8B-Instruct-raccis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use raulgdp/Ministral-8B-Instruct-raccis with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Ministral-8B-Instruct-2410") model = PeftModel.from_pretrained(base_model, "raulgdp/Ministral-8B-Instruct-raccis") - Notebooks
- Google Colab
- Kaggle
End of training
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README.md
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# Ministral-8B-Instruct-raccis
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This model is a fine-tuned version of [mistralai/Ministral-8B-Instruct-2410](https://huggingface.co/mistralai/Ministral-8B-Instruct-2410) on
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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### Training results
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| Training Loss | Epoch
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### Framework versions
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# Ministral-8B-Instruct-raccis
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This model is a fine-tuned version of [mistralai/Ministral-8B-Instruct-2410](https://huggingface.co/mistralai/Ministral-8B-Instruct-2410) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.1830
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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| 2.2547 | 1.7336 | 100 | 2.3270 |
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| 2.1866 | 3.4541 | 200 | 2.2232 |
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| 2.0063 | 5.1747 | 300 | 2.1858 |
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| 1.9367 | 6.9083 | 400 | 2.1675 |
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| 1.88 | 8.6288 | 500 | 2.1830 |
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### Framework versions
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adapter_model.safetensors
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