Instructions to use HugoStiglitz/lora_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HugoStiglitz/lora_model2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("HugoStiglitz/lora_model2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use HugoStiglitz/lora_model2 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 HugoStiglitz/lora_model2 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 HugoStiglitz/lora_model2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for HugoStiglitz/lora_model2 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="HugoStiglitz/lora_model2", max_seq_length=2048, )
Update config.json
Browse files- config.json +1 -0
config.json
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"up_proj",
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"k_proj",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"model_type": llama,
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"target_modules": [
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"up_proj",
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"k_proj",
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