Instructions to use mjwong/multilingual-e5-large-instruct-xnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mjwong/multilingual-e5-large-instruct-xnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="mjwong/multilingual-e5-large-instruct-xnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mjwong/multilingual-e5-large-instruct-xnli") model = AutoModelForSequenceClassification.from_pretrained("mjwong/multilingual-e5-large-instruct-xnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:2fb12659584e3b8d01e46e09de85b505b8ac57cf48dd18a8c751482af6274570
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size 2239626972
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