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 cross/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/cross/tokenizer.json
- Command line
-
hf download hf://usejul/jul-decision-e5-small/cross/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/usejul/jul-decision-e5-small/resolve/main/cross/tokenizer.json
17.1 MB
- Xet hash:
- 20c5ce2f70e3ab9c910d81344b8aec97066b4b7aeadc56264132ae16db0b6748
- Size of remote file:
- 17.1 MB
- SHA256:
- fb02bfe42ffe0fe115de5c74f76c6480d730e60cc1f6ae567ff4d82cb305a113
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