Instructions to use furrutiav/neobert_mixtral_nllfg_rubric_rte_sentence_embd_perplexity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use furrutiav/neobert_mixtral_nllfg_rubric_rte_sentence_embd_perplexity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="furrutiav/neobert_mixtral_nllfg_rubric_rte_sentence_embd_perplexity", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("furrutiav/neobert_mixtral_nllfg_rubric_rte_sentence_embd_perplexity", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49d7ae5ae093833c308b933f121ba92f173ddd8e5c346a8d9c53d40037a55788
- Size of remote file:
- 887 MB
- SHA256:
- 6ac14950a0ae0d91135bdd2f39002c1fe3c145beedd61e44166ec5fc4d253706
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