Instructions to use CeroShrijver/m3e-base-text-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CeroShrijver/m3e-base-text-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CeroShrijver/m3e-base-text-classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CeroShrijver/m3e-base-text-classification") model = AutoModelForSequenceClassification.from_pretrained("CeroShrijver/m3e-base-text-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CeroShrijver/m3e-base-text-classification: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/CeroShrijver/m3e-base-text-classification/resolve/refs%2Fpr%2F1/training_args.bin
- Command line
-
hf download hf://CeroShrijver/m3e-base-text-classification@refs/pr/1/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/CeroShrijver/m3e-base-text-classification/resolve/refs%2Fpr%2F1/training_args.bin
3.96 kB
- Xet hash:
- e303d0d3e9d88b0c554b2629a8493b1537d5d72761d5c7e283464144055cf270
- Size of remote file:
- 3.96 kB
- SHA256:
- a9508f96bc81e7e124e0c1d6b02bd79a7a2bfc941a52125c2e8409d50c403a6f
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