Instructions to use PowCal/deepseek-coder-6.7b-base-4bit-code-sft-ce-code-dpo-ipo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PowCal/deepseek-coder-6.7b-base-4bit-code-sft-ce-code-dpo-ipo with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PowCal/deepseek-coder-6.7b-base-4bit-code-sft-ce-code-dpo-ipo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- adapter_config.json +4 -4
- adapter_model.safetensors +1 -1
- reference/adapter_config.json +4 -4
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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"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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"q_proj",
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"k_proj",
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"v_proj",
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"down_proj"
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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 80014016
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version https://git-lfs.github.com/spec/v1
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oid sha256:6cc43c6562227ca13b9a70724f9c9d5a2155d83a33dd9b54d7f7ad5d1ae15794
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size 80014016
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reference/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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"q_proj",
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"
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"k_proj",
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"gate_proj",
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"v_proj",
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"
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"o_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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+
"gate_proj",
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"q_proj",
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+
"up_proj",
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"o_proj",
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"k_proj",
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"v_proj",
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+
"down_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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