Instructions to use funnel-transformer/medium-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/medium-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/medium-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/medium-base") model = AutoModel.from_pretrained("funnel-transformer/medium-base") - Notebooks
- Google Colab
- Kaggle
Updates incorrect tokenizer configuration file (#1)
Browse files- Adds tokenizer_config.json file (e06079ddb72e77eea4d0c7981cdd82d41aef6c0a)
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tokenizer_config.json
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{"unk_token": "<unk>", "sep_token": "<sep>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": "<mask>", "bos_token": "<s>", "eos_token": "</s>"}
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{"unk_token": "<unk>", "sep_token": "<sep>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": "<mask>", "bos_token": "<s>", "eos_token": "</s>", "do_lower_case": true, "model_max_length": 512}
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