Instructions to use Recognai/zeroshot_selectra_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Recognai/zeroshot_selectra_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Recognai/zeroshot_selectra_small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Recognai/zeroshot_selectra_small") model = AutoModelForSequenceClassification.from_pretrained("Recognai/zeroshot_selectra_small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Recognai/zeroshot_selectra_small: direct link, hf CLI and curl.
- Browser
- Download file 90 MB
-
https://huggingface.co/Recognai/zeroshot_selectra_small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Recognai/zeroshot_selectra_small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Recognai/zeroshot_selectra_small/resolve/main/pytorch_model.bin
90 MB
- Xet hash:
- fea9fac9b0f99a6f8f717fe34bd750212ddab78cbaaf81c7bf1bce512e5fc118
- Size of remote file:
- 90 MB
- SHA256:
- 729c69f558d1cec52ded9976a0f27c1fb024ab1786cb825e7b334db5a7041737
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