Instructions to use papinwit/ner_lora_model_27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use papinwit/ner_lora_model_27b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("papinwit/ner_lora_model_27b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use papinwit/ner_lora_model_27b 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 papinwit/ner_lora_model_27b 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 papinwit/ner_lora_model_27b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for papinwit/ner_lora_model_27b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="papinwit/ner_lora_model_27b", max_seq_length=2048, )
- Xet hash:
- 234ee0aa293bf03a53adca5fc0077b39c366ded6066cfb33cee815003e7fd5cc
- Size of remote file:
- 537 MB
- SHA256:
- 20c6ec581ef8e51f20754a5b2b8de1fee11032338469da14abb8f3f05dfc3991
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