Instructions to use VERSIL91/451b2c8d-4afc-4be1-8057-ec8d6752d915 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VERSIL91/451b2c8d-4afc-4be1-8057-ec8d6752d915 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama") model = PeftModel.from_pretrained(base_model, "VERSIL91/451b2c8d-4afc-4be1-8057-ec8d6752d915") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +4 -4
- adapter_model.bin +1 -1
README.md
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This model is a fine-tuned version of [unsloth/tinyllama](https://huggingface.co/unsloth/tinyllama) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 8.9412 | 0.0615 | 1 | 8.9477 |
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### Framework versions
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This model is a fine-tuned version of [unsloth/tinyllama](https://huggingface.co/unsloth/tinyllama) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7484
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## Model description
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:------:|:----:|:---------------:|
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| 8.9412 | 0.0615 | 1 | 8.9477 |
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| 7.4528 | 0.3077 | 5 | 7.1644 |
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| 3.8 | 0.6154 | 10 | 3.3564 |
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| 1.6571 | 0.9231 | 15 | 1.7484 |
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### Framework versions
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adapter_model.bin
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