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alexanderyj
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gemma3_fine_tuning2025-05-23

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Generated from Trainer
trl
sft
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  1. .gitattributes +1 -0
  2. README.md +58 -0
  3. adapter_config.json +37 -0
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  8. processor_config.json +4 -0
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  37. special_tokens_map.json +33 -0
  38. tokenizer.json +3 -0
  39. tokenizer.model +3 -0
  40. tokenizer_config.json +0 -0
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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ base_model: google/gemma-3-4b-it
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+ library_name: transformers
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+ model_name: gemma3_fine_tuning2025-05-23
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+ tags:
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+ - generated_from_trainer
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+ - trl
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+ - sft
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+ licence: license
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+ ---
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+
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+ # Model Card for gemma3_fine_tuning2025-05-23
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+
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+ This model is a fine-tuned version of [google/gemma-3-4b-it](https://huggingface.co/google/gemma-3-4b-it).
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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+ generator = pipeline("text-generation", model="alexanderyj/gemma3_fine_tuning2025-05-23", device="cuda")
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+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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+ print(output["generated_text"])
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+ ```
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+
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+ ## Training procedure
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+
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+
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+
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+
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+ This model was trained with SFT.
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+
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+ ### Framework versions
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+
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+ - TRL: 0.17.0
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+ - Transformers: 4.51.3
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+ - Pytorch: 2.7.0
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+ - Datasets: 3.6.0
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+ - Tokenizers: 0.21.1
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+
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+ ## Citations
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+
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+
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+
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+ Cite TRL as:
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+
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+ ```bibtex
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+ @misc{vonwerra2022trl,
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+ title = {{TRL: Transformer Reinforcement Learning}},
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+ author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
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+ year = 2020,
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+ journal = {GitHub repository},
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+ publisher = {GitHub},
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+ howpublished = {\url{https://github.com/huggingface/trl}}
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+ }
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+ ```
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