Instructions to use Unbabel/xlm-roberta-comet-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Unbabel/xlm-roberta-comet-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Unbabel/xlm-roberta-comet-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Unbabel/xlm-roberta-comet-small") model = AutoModel.from_pretrained("Unbabel/xlm-roberta-comet-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Unbabel/xlm-roberta-comet-small: direct link, hf CLI and curl.
- Browser
- Download file 392 Bytes
-
https://huggingface.co/Unbabel/xlm-roberta-comet-small/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Unbabel/xlm-roberta-comet-small/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/Unbabel/xlm-roberta-comet-small/resolve/main/tokenizer_config.json
392 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "nreimers/mMiniLMv2-L6-H384-distilled-from-XLMR-Large"} |