Instructions to use bilkultheek/Cold-Data-LLama-2-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use bilkultheek/Cold-Data-LLama-2-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "bilkultheek/Cold-Data-LLama-2-7B") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 20
Browse files- adapter_config.json +2 -2
- adapter_model.safetensors +1 -1
- tokenizer.json +2 -2
- 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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"k_proj",
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"q_proj",
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"v_proj"
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],
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"task_type": "SEQ_CLS",
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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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"v_proj",
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"k_proj"
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],
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"task_type": "SEQ_CLS",
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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 201385536
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version https://git-lfs.github.com/spec/v1
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oid sha256:1fbe8baccdfad589e4feb150825eb57af6dfb880185ce0040bb60d4ea0a06143
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size 201385536
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tokenizer.json
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length":
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"strategy": "LongestFirst",
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"stride": 0
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},
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"padding": {
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"strategy": {
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"Fixed":
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},
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"direction": "Right",
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"pad_to_multiple_of": null,
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length": 900,
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"strategy": "LongestFirst",
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"stride": 0
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},
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"padding": {
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"strategy": {
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"Fixed": 900
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},
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"direction": "Right",
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"pad_to_multiple_of": null,
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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 5432
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version https://git-lfs.github.com/spec/v1
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oid sha256:1df3b6eb12d694cd271d02b60e1d27d802ef1c30f575b7ffed354e2041d3d410
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size 5432
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