Instructions to use matteodagos/M3_stem_aligned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use matteodagos/M3_stem_aligned with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for matteodagos/M3_stem_aligned to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for matteodagos/M3_stem_aligned to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for matteodagos/M3_stem_aligned to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="matteodagos/M3_stem_aligned", max_seq_length=2048, )
Upload model trained with Unsloth
Browse filesUpload model trained with Unsloth 2x faster
- tokenizer_config.json +0 -1
tokenizer_config.json
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"padding_side": "right",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"torch_dtype": "auto",
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"unk_token": null
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}
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"padding_side": "right",
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"split_special_tokens": false,
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"tokenizer_class": "Qwen2Tokenizer",
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"unk_token": null
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}
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