Instructions to use funnel-transformer/large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use funnel-transformer/large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="funnel-transformer/large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("funnel-transformer/large") model = AutoModel.from_pretrained("funnel-transformer/large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from funnel-transformer/large: direct link, hf CLI and curl.
- Browser
- Download file 201 Bytes
-
https://huggingface.co/funnel-transformer/large/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://funnel-transformer/large/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/funnel-transformer/large/resolve/main/tokenizer_config.json
201 Bytes
| {"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} |