Training in progress, step 39
Browse files- .gitattributes +1 -0
- README.md +58 -0
- adapter_config.json +46 -0
- adapter_model.safetensors +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +13 -0
- training_args.bin +3 -0
.gitattributes
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README.md
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---
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base_model: meta-llama/Llama-3.2-1B
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library_name: transformers
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model_name: llama_3.2_1B
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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 llama_3.2_1B
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This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B).
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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="guilhermenf/llama_3.2_1B", 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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This model was trained with SFT.
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### Framework versions
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- TRL: 0.29.1
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- Transformers: 5.3.0
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- Pytorch: 2.9.0+cu126
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- Datasets: 4.8.3
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- Tokenizers: 0.22.2
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## Citations
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Cite TRL as:
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```bibtex
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@software{vonwerra2020trl,
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title = {{TRL: Transformers Reinforcement Learning}},
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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license = {Apache-2.0},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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```
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adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": null,
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"base_model_name_or_path": "meta-llama/Llama-3.2-1B",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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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": 32,
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"lora_bias": false,
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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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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"q_proj",
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"o_proj",
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"k_proj",
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"down_proj",
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"gate_proj",
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"up_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:1ac8f840f8c6a6df1a4964404f47d1e41788022a56f0bb9fe4ca02f6aab54441
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size 22574152
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
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size 17209920
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tokenizer_config.json
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{
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"backend": "tokenizers",
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"bos_token": "<|begin_of_text|>",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|end_of_text|>",
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"is_local": false,
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"model_input_names": [
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"input_ids",
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"attention_mask"
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],
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"model_max_length": 131072,
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"tokenizer_class": "TokenizersBackend"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:77f1ffa9b8c31861d7e8b4f27cadbc15cb743279c2c1d23f488ecb22308db007
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size 5713
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