Text Classification
Transformers
PyTorch
TensorFlow
Safetensors
English
t5
text2text-generation
token-classification
question-answering
text-generation
Instructions to use razent/SciFive-base-PMC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razent/SciFive-base-PMC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="razent/SciFive-base-PMC")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("razent/SciFive-base-PMC") model = AutoModelForSeq2SeqLM.from_pretrained("razent/SciFive-base-PMC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (7b5edcbd070122d106d17ea4bf8d62f8528b0be7) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>dcf890f
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Update README.md (#1)
- Update README.md (ce746855159bef1b094a044f770144313f73dbf5) Co-authored-by: Long Phan <justinphan3110@users.noreply.huggingface.co>7fe8d55
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Update config.json
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Update README.md
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update models
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Initialize model
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initial commit
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