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  1. Add quantized model /home/llama3.2-pyfim-3b/llama3.2-pyfim-3B-Q8_0.gguf

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  2. Upload tokenizer

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  3. Update tokenizer_config.json

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  4. Model at step: 9369 on file data_1.csv (Trained with Unsloth)

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  5. Model at step: 9000 on file data_1.csv (Trained with Unsloth)

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  6. Model at step: 8500 on file data_1.csv (Trained with Unsloth)

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  7. Model at step: 8000 on file data_1.csv (Trained with Unsloth)

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  8. Model at step: 7500 on file data_1.csv (Trained with Unsloth)

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  9. Model at step: 7000 on file data_1.csv (Trained with Unsloth)

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  10. Model at step: 6500 on file data_1.csv (Trained with Unsloth)

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  11. Model at step: 6000 on file data_1.csv (Trained with Unsloth)

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  12. Model at step: 5500 on file data_1.csv (Trained with Unsloth)

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  13. Model at step: 5000 on file data_1.csv (Trained with Unsloth)

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  14. Model at step: 4500 on file data_1.csv (Trained with Unsloth)

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  15. Model at step: 4000 on file data_1.csv (Trained with Unsloth)

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  16. Model at step: 3500 on file data_1.csv (Trained with Unsloth)

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  17. Model at step: 3000 on file data_1.csv (Trained with Unsloth)

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  18. Model at step: 2500 on file data_1.csv (Trained with Unsloth)

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  19. Model at step: 2000 on file data_1.csv (Trained with Unsloth)

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  20. Model at step: 1500 on file data_1.csv (Trained with Unsloth)

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  21. Model at step: 1000 on file data_1.csv (Trained with Unsloth)

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  22. Model at step: 500 on file data_1.csv (Trained with Unsloth)

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  1. Trained with Unsloth

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  2. Upload tokenizer

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  3. Update tokenizer_config.json

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  4. Update tokenizer_config.json

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  5. Upload 3 files

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  6. Upload tokenizer.json⁠

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  7. Upload tokenizer

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  8. initial commit

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