Instructions to use pysentimiento/robertuito-pos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pysentimiento/robertuito-pos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="pysentimiento/robertuito-pos")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("pysentimiento/robertuito-pos") model = AutoModelForTokenClassification.from_pretrained("pysentimiento/robertuito-pos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from pysentimiento/robertuito-pos: direct link, hf CLI and curl.
- Browser
- Download file 330 Bytes
-
https://huggingface.co/pysentimiento/robertuito-pos/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://pysentimiento/robertuito-pos/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/pysentimiento/robertuito-pos/resolve/main/tokenizer_config.json
330 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "special_tokens_map_file": "models/twerto-base-cased/special_tokens_map.json", "name_or_path": "pysentimiento/robertuito-base-cased", "tokenizer_class": "PreTrainedTokenizerFast"} |