Instructions to use malteos/aspect-scibert-task with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malteos/aspect-scibert-task with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="malteos/aspect-scibert-task")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("malteos/aspect-scibert-task") model = AutoModel.from_pretrained("malteos/aspect-scibert-task", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (e5002be40cd1de5a51f7e07f4af53ebebcd93dbf) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>15ccf71
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Upload pytorch_model.bin with git-lfs
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Upload vocab.txt
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Upload tokenizer_config.json
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Upload special_tokens_map.json
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Upload config.json
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Update README.md
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initial commit
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