Zero-Shot Classification
Transformers
Safetensors
English
French
multilingual
bert
feature-extraction
jul
Instructions to use usejul/jul-decision-e5-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usejul/jul-decision-e5-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="usejul/jul-decision-e5-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("usejul/jul-decision-e5-small") model = AutoModel.from_pretrained("usejul/jul-decision-e5-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from usejul/jul-decision-e5-small: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/usejul/jul-decision-e5-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://usejul/jul-decision-e5-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/usejul/jul-decision-e5-small/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 58cedf6a5f0421aed26d6136bb7bdce553daf670be888e75f359f60f8279de67
- Size of remote file:
- 17.1 MB
- SHA256:
- 6040ba36e3e2f7b2fa6ae076b69d024a08666bea4c345105a32e542900fcc7e7
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