Instructions to use ACampero/debug_test_masking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ACampero/debug_test_masking with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ACampero/debug_test_masking", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use ACampero/debug_test_masking 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 ACampero/debug_test_masking 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 ACampero/debug_test_masking to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for ACampero/debug_test_masking to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="ACampero/debug_test_masking", max_seq_length=2048, )
- Xet hash:
- e5381c2274d4916f7e96c71573c828516006021aa5fee3b07e9defcf1ddfbbfa
- Size of remote file:
- 5.97 kB
- SHA256:
- 237823036dfbdc6f800a52b8244996eb13e4a4706b4bec78813e7f1af9686343
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.