Instructions to use canIjoin/datafun with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use canIjoin/datafun with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="canIjoin/datafun")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("canIjoin/datafun") model = AutoModelForTokenClassification.from_pretrained("canIjoin/datafun", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from canIjoin/datafun: direct link, hf CLI and curl.
- Browser
- Download file 157 Bytes
-
https://huggingface.co/canIjoin/datafun/resolve/main/.gitattributes
- Command line
-
hf download hf://canIjoin/datafun/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/canIjoin/datafun/resolve/main/.gitattributes
157 Bytes
| flax_model.msgpack filter=lfs diff=lfs merge=lfs -text | |
| pytorch_model.bin filter=lfs diff=lfs merge=lfs -text | |
| tf_model.h5 filter=lfs diff=lfs merge=lfs -text | |