Instructions to use hsila/chembed-full-e6-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hsila/chembed-full-e6-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hsila/chembed-full-e6-6", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hsila/chembed-full-e6-6", trust_remote_code=True) model = AutoModel.from_pretrained("hsila/chembed-full-e6-6", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Add sentence-transformer file sentence_bert_config.json
Browse files
sentence_bert_config.json
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{
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"max_seq_length": 8192,
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"do_lower_case": false
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}
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