Instructions to use tmasis/geocoding-complex-location-references with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- Unsloth Studio
How to use tmasis/geocoding-complex-location-references 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 tmasis/geocoding-complex-location-references 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 tmasis/geocoding-complex-location-references to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tmasis/geocoding-complex-location-references to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="tmasis/geocoding-complex-location-references", max_seq_length=2048, )
Update README.md
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README.md
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# Load model from Huggingface Hub
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model, tokenizer = FastLanguageModel.from_pretrained(
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FastLanguageModel.for_inference(model)
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messages = [{"role": "system", "content": <system_prompt>},
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# Load model from Huggingface Hub
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model, tokenizer = FastLanguageModel.from_pretrained(
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model_name = "tmasis/geocoding-complex-location-references",
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max_seq_length = 2048,
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load_in_4bit = True)
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FastLanguageModel.for_inference(model)
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messages = [{"role": "system", "content": <system_prompt>},
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