Instructions to use tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b") model = PeftModel.from_pretrained(base_model, "tarabukinivan/d7d0741c-b0e3-40c8-82c3-1dec958d7df0") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 15
Browse files- adapter_config.json +4 -4
- training_args.bin +1 -1
adapter_config.json
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"down_proj",
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"o_proj",
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"q_proj",
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"
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"v_proj",
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"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"o_proj",
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"q_proj",
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"down_proj",
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"up_proj",
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"v_proj",
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"k_proj",
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"gate_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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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:
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size 6776
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version https://git-lfs.github.com/spec/v1
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oid sha256:97252989f4b5e78a81f33ffdc9b344577f92ae0b70be3d300fd4e3ad66cd6604
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size 6776
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