Instructions to use NorGLM/Entailment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NorGLM/Entailment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NorGLM/Entailment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NorGLM/Entailment") model = AutoModelForSequenceClassification.from_pretrained("NorGLM/Entailment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download README from NorGLM/Entailment: direct link, hf CLI and curl.
- Browser
- Download file 395 Bytes
-
https://huggingface.co/NorGLM/Entailment/resolve/main/README
- Command line
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hf download hf://NorGLM/Entailment/README
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curl -L -o README https://huggingface.co/NorGLM/Entailment/resolve/main/README
395 Bytes
| This archive is part of the NLPL Word Vectors Repository (http://vectors.nlpl.eu/repository/), version 2.0, published on Friday, December 27, 2019. | |
| Please see the file 'meta.json' in this archive and the overall repository metadata file http://vectors.nlpl.eu/repository/20.json for additional information. | |
| The life-time identifier for this model is: | |
| http://vectors.nlpl.eu/repository/20/221.zip |