Instructions to use sindsub/cybersec-grouper-federated-static-round3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sindsub/cybersec-grouper-federated-static-round3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sindsub/cybersec-grouper-federated-static-round3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- adapter_config.json +3 -3
- adapter_model.safetensors +2 -2
adapter_config.json
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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": "Qwen/
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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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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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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": "Qwen/Qwen2.5-1.5B-Instruct",
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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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"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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],
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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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version https://git-lfs.github.com/spec/v1
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oid sha256:128c8fee8d39f36afa33215ba23f80cd79f84b1fb4eab7c0c4c8ef8e8dcab500
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size 8731128
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