Instructions to use oeg/software_benchmark_bio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oeg/software_benchmark_bio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="oeg/software_benchmark_bio")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("oeg/software_benchmark_bio") model = AutoModelForTokenClassification.from_pretrained("oeg/software_benchmark_bio") - Notebooks
- Google Colab
- Kaggle
Folder software_benchmark removed
Browse files- benchmark_model/config.json β config.json +0 -0
- benchmark_model/pytorch_model.bin β pytorch_model.bin +0 -0
- benchmark_model/special_tokens_map.json β special_tokens_map.json +0 -0
- benchmark_model/tokenizer.json β tokenizer.json +0 -0
- benchmark_model/tokenizer_config.json β tokenizer_config.json +0 -0
- benchmark_model/training_args.bin β training_args.bin +0 -0
- benchmark_model/vocab.txt β vocab.txt +0 -0
benchmark_model/config.json β config.json
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benchmark_model/pytorch_model.bin β pytorch_model.bin
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benchmark_model/special_tokens_map.json β special_tokens_map.json
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benchmark_model/tokenizer.json β tokenizer.json
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benchmark_model/tokenizer_config.json β tokenizer_config.json
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benchmark_model/training_args.bin β training_args.bin
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benchmark_model/vocab.txt β vocab.txt
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