Instructions to use viswavi/datafinder-scibert-nl-queries-dataset-description-only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use viswavi/datafinder-scibert-nl-queries-dataset-description-only with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="viswavi/datafinder-scibert-nl-queries-dataset-description-only")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("viswavi/datafinder-scibert-nl-queries-dataset-description-only") model = AutoModel.from_pretrained("viswavi/datafinder-scibert-nl-queries-dataset-description-only", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from viswavi/datafinder-scibert-nl-queries-dataset-description-only: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/viswavi/datafinder-scibert-nl-queries-dataset-description-only/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://viswavi/datafinder-scibert-nl-queries-dataset-description-only/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/viswavi/datafinder-scibert-nl-queries-dataset-description-only/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- bcf0afc42cbb2237d25e4ee2afc991ca3736916754241d86eddf999948164dcc
- Size of remote file:
- 440 MB
- SHA256:
- 330840eb78d061e7187220ad6c2091618fdfbef9fa73fde2145302e9323a0e03
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