Instructions to use lmassaron/coder-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmassaron/coder-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lmassaron/coder-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- adapter_config.json +6 -6
- 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/Qwen3
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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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"down_proj",
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"up_proj",
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"v_proj",
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"o_proj",
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"q_proj",
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"gate_proj",
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"k_proj"
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],
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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/Qwen3-4B",
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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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"o_proj",
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"gate_proj",
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"k_proj",
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"down_proj",
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"up_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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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:3491fedb2cfdd7052d07a4fc8c4f1430996ec262f92d06d270266c984703b6c5
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size 66127776
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