Instructions to use furrutiav/neobert_mixtral_nllfg_vanilla_mrpc_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_mrpc_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_mrpc_tf_idf_centroid", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("furrutiav/neobert_mixtral_nllfg_vanilla_mrpc_tf_idf_centroid", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a163e8bf7203e5ad8cdc500913f258fdd7a3fe321fbced895fe3bfe97c37b39
- Size of remote file:
- 887 MB
- SHA256:
- be4e49e3ab7617f6d73b1a15335ea73fd231b3ec7da7c6e032ef080da73e4dd0
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