Instructions to use allenai/specter2_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/specter2_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="allenai/specter2_base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("allenai/specter2_base") model = AutoModel.from_pretrained("allenai/specter2_base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from allenai/specter2_base: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/allenai/specter2_base/resolve/refs%2Fpr%2F5/pytorch_model.bin
- Command line
-
hf download hf://allenai/specter2_base@refs/pr/5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/allenai/specter2_base/resolve/refs%2Fpr%2F5/pytorch_model.bin
440 MB
- Xet hash:
- 92a724a80d85cfc6d11745fa6e9bfabec84a96abbfdaa26c8cba4e64d4e6432e
- Size of remote file:
- 440 MB
- SHA256:
- 801eda968fad1752fe846a8e572bfdc25202be85544680dda4c99f4589646ebc
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