Instructions to use fqb/las_lora_model_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fqb/las_lora_model_100 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fqb/las_lora_model_100", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use fqb/las_lora_model_100 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 fqb/las_lora_model_100 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 fqb/las_lora_model_100 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for fqb/las_lora_model_100 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="fqb/las_lora_model_100", max_seq_length=2048, )
- Xet hash:
- 50104411a882497d0b5cc2bfc1c26cd99780a9939b3f582fad416d5c279ee1aa
- Size of remote file:
- 11.7 MB
- SHA256:
- 0eb76a326a87b6d1cb1874e097c9c7db414956821d51792ad3d29d012bd2a756
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