Instructions to use UT/BMW with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UT/BMW with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UT/BMW")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UT/BMW") model = AutoModelForSequenceClassification.from_pretrained("UT/BMW", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from UT/BMW: direct link, hf CLI and curl.
- Browser
- Download file 238 Bytes
-
https://huggingface.co/UT/BMW/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://UT/BMW/special_tokens_map.json
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curl -L -o special_tokens_map.json https://huggingface.co/UT/BMW/resolve/main/special_tokens_map.json
238 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true}} |