Instructions to use google/canine-s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/canine-s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="google/canine-s")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("google/canine-s") model = AutoModel.from_pretrained("google/canine-s", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from google/canine-s: direct link, hf CLI and curl.
- Browser
- Download file 657 Bytes
-
https://huggingface.co/google/canine-s/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://google/canine-s/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/google/canine-s/resolve/main/special_tokens_map.json
657 Bytes
| {"bos_token": {"content": "", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "eos_token": {"content": "", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "sep_token": {"content": "", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "pad_token": {"content": "\u0000", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "cls_token": {"content": "", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, "mask_token": {"content": "", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}} |