Instructions to use huggingface/funnel-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huggingface/funnel-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="huggingface/funnel-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("huggingface/funnel-small") model = AutoModel.from_pretrained("huggingface/funnel-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from huggingface/funnel-small: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/huggingface/funnel-small/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://huggingface/funnel-small/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/huggingface/funnel-small/resolve/main/tokenizer_config.json
48 Bytes
| {"do_lower_case": true, "model_max_length": 512} |