Instructions to use Labib11/PMC_GIST with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Labib11/PMC_GIST with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Labib11/PMC_GIST")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Labib11/PMC_GIST") model = AutoModel.from_pretrained("Labib11/PMC_GIST", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download sentence_bert_config.json from Labib11/PMC_GIST: direct link, hf CLI and curl.
- Browser
- Download file 53 Bytes
-
https://huggingface.co/Labib11/PMC_GIST/resolve/main/sentence_bert_config.json
- Command line
-
hf download hf://Labib11/PMC_GIST/sentence_bert_config.json
-
curl -L -o sentence_bert_config.json https://huggingface.co/Labib11/PMC_GIST/resolve/main/sentence_bert_config.json
53 Bytes
| { | |
| "max_seq_length": 512, | |
| "do_lower_case": false | |
| } |