Instructions to use s2510436/3333 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use s2510436/3333 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("s2510436/3333", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 50
Browse files- adapter_config.json +7 -7
- adapter_model.safetensors +1 -1
- 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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"o_proj",
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"proj",
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"
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"
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"qkv",
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"
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"up_proj",
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"
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"gate_proj",
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"
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"q_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"proj",
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"v_proj",
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"o_proj",
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"fc2",
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"qkv",
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"k_proj",
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"q_proj",
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"up_proj",
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"down_proj",
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"gate_proj",
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"fc1"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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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 232011776
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:2704d802d8de248f4ab70d9d2444a45b1117f9d52dc95656f2135b0de10808b4
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size 232011776
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training_args.bin
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@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size 6161
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:9682d8d72159bc2316c74e94a465004c1227ee8365d924436184d2fc23aec0b3
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size 6161
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