Instructions to use michlea/HidatoQwenModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michlea/HidatoQwenModel with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("michlea/HidatoQwenModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Training in progress, step 1000, checkpoint
Browse files- last-checkpoint/adapter_config.json +5 -5
- last-checkpoint/adapter_model.safetensors +1 -1
- last-checkpoint/optimizer.pt +2 -2
- last-checkpoint/rng_state.pth +1 -1
- last-checkpoint/scaler.pt +1 -1
- last-checkpoint/scheduler.pt +1 -1
- last-checkpoint/trainer_state.json +0 -0
- last-checkpoint/training_args.bin +1 -1
last-checkpoint/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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"o_proj",
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"up_proj"
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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last-checkpoint/adapter_model.safetensors
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last-checkpoint/optimizer.pt
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last-checkpoint/rng_state.pth
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last-checkpoint/scaler.pt
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last-checkpoint/scheduler.pt
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last-checkpoint/trainer_state.json
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last-checkpoint/training_args.bin
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