Instructions to use sravanthib/testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sravanthib/testing with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "sravanthib/testing") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 10
Browse files- adapter_config.json +4 -4
- adapter_model.safetensors +1 -1
- metrics.json +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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"
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"gate_proj",
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"down_proj",
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"v_proj",
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"up_proj",
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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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"q_proj",
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"o_proj",
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"gate_proj",
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"v_proj",
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"k_proj",
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"up_proj",
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"down_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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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:
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size 11301520
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version https://git-lfs.github.com/spec/v1
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oid sha256:4bb995fc96df85d46d015c0ae36e86d50566788ed4569be1528215b051754757
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size 11301520
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metrics.json
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{"run_name": "/data-shared/testing-refactored", "train_runtime":
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{"run_name": "/data-shared/testing-refactored", "train_runtime": 76.5183, "train_samples_per_second": 5.228, "train_steps_per_second": 0.131, "total_flos": 4810910442979328.0, "train_loss": 3.0876850128173827, "epoch": 0.01, "total_training_time": 82.92802095413208, "total_training_time_mins": 1.382133682568868, "avg_step_time": 7.034697532653809}
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