Instructions to use halimara/model_sentence_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halimara/model_sentence_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="halimara/model_sentence_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("halimara/model_sentence_bert") model = AutoModel.from_pretrained("halimara/model_sentence_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download unigram.json from halimara/model_sentence_bert: direct link, hf CLI and curl.
- Browser
- Download file 14.8 MB
-
https://huggingface.co/halimara/model_sentence_bert/resolve/main/unigram.json
- Command line
-
hf download hf://halimara/model_sentence_bert/unigram.json
-
curl -L -o unigram.json https://huggingface.co/halimara/model_sentence_bert/resolve/main/unigram.json
14.8 MB
- Xet hash:
- 303c2c1342c3411d08077fdbae9b292c26f1d198acc653311731c7b7d9734f38
- Size of remote file:
- 14.8 MB
- SHA256:
- 71b44701d7efd054205115acfa6ef126c5d2f84bd3affe0c59e48163674d19a6
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