Instructions to use hanzceo/JOSS-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hanzceo/JOSS-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hanzceo/JOSS-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hanzceo/JOSS-v1") model = AutoModelForSequenceClassification.from_pretrained("hanzceo/JOSS-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from hanzceo/JOSS-v1: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/hanzceo/JOSS-v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://hanzceo/JOSS-v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/hanzceo/JOSS-v1/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 035d892ae08cd33ccb79c09f28d6824d8e91751c07011820320d8dc8d50a7a28
- Size of remote file:
- 11.4 MB
- SHA256:
- b7a6a993d40b42d517297bb247ff66679e5bc9dd7a5143be0620faf210b42861
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