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 flax_model.msgpack from canIjoin/datafun: direct link, hf CLI and curl.
- Browser
- Download file 407 MB
-
https://huggingface.co/canIjoin/datafun/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://canIjoin/datafun@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/canIjoin/datafun/resolve/refs%2Fpr%2F1/flax_model.msgpack
407 MB
- Xet hash:
- ed40ef302663b4560cac92741971a25a3cff1319698d1505010e20f1de2cedef
- Size of remote file:
- 407 MB
- SHA256:
- 3fcc5a4fdb2a83463bf4f65ea0d60e3ecb31963cf85f4f513f3b48150b522b57
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