smsk-01/gemma-3-1b-ft-yiddish
Browse files- .gitattributes +1 -0
- README.md +58 -0
- adapter_config.json +34 -0
- adapter_model.safetensors +3 -0
- added_tokens.json +3 -0
- runs/Apr06_13-20-00_435d53d616ab/events.out.tfevents.1743945776.435d53d616ab.623.1 +3 -0
- runs/Apr06_16-20-03_fb1f2268705f/events.out.tfevents.1743956500.fb1f2268705f.1489.0 +3 -0
- runs/Apr06_18-34-16_4b372abc422d/events.out.tfevents.1743964534.4b372abc422d.6504.0 +3 -0
- runs/Apr06_19-54-31_6d3a02d49539/events.out.tfevents.1743969353.6d3a02d49539.5207.0 +3 -0
- special_tokens_map.json +33 -0
- tokenizer.json +3 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
- training_args.bin +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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base_model: google/gemma-3-1b-it
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library_name: transformers
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model_name: gemma-3b-qlora-finetuned
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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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# Model Card for gemma-3b-qlora-finetuned
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This model is a fine-tuned version of [google/gemma-3-1b-it](https://huggingface.co/google/gemma-3-1b-it).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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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="smsk-01/gemma-3b-qlora-finetuned", 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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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/s-lhayani2-bureau-des-el-ves-mines-paristech/huggingface/runs/v5hcbf5y)
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This model was trained with SFT.
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### Framework versions
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- TRL: 0.16.1
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- Transformers: 4.51.0
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- Pytorch: 2.6.0+cu124
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- Datasets: 3.5.0
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- Tokenizers: 0.21.1
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## Citations
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Cite TRL as:
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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 Gallouédec},
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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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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"bias": "none",
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"eva_config": null,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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{
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runs/Apr06_13-20-00_435d53d616ab/events.out.tfevents.1743945776.435d53d616ab.623.1
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special_tokens_map.json
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tokenizer_config.json
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training_args.bin
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