Instructions to use bn22/experimental-te-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bn22/experimental-te-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bn22/experimental-te-ft")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bn22/experimental-te-ft") model = AutoModel.from_pretrained("bn22/experimental-te-ft") - Notebooks
- Google Colab
- Kaggle
File size: 322 Bytes
ee62e0b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": "<|startoftext|>",
"do_lower_case": true,
"eos_token": "<|endoftext|>",
"errors": "replace",
"is_local": false,
"model_max_length": 77,
"pad_token": "<|endoftext|>",
"tokenizer_class": "CLIPTokenizer",
"unk_token": "<|endoftext|>"
}
|