Instructions to use furrutiav/neobert_mixtral_nllfg_vanilla_qnli_tf_idf_centroid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use furrutiav/neobert_mixtral_nllfg_vanilla_qnli_tf_idf_centroid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="furrutiav/neobert_mixtral_nllfg_vanilla_qnli_tf_idf_centroid", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("furrutiav/neobert_mixtral_nllfg_vanilla_qnli_tf_idf_centroid", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- afe6dcdbfd832c363a35220ec7db8b1af612e3c0c066d77209a0d3daf1aa7b69
- Size of remote file:
- 887 MB
- SHA256:
- 3359d9d904a1b44876d66003a36c8ad1575bf464f25eb9aab08f5d2a34b78315
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