Instructions to use tr3cks/SentimentAnalysis_BETO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tr3cks/SentimentAnalysis_BETO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tr3cks/SentimentAnalysis_BETO")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tr3cks/SentimentAnalysis_BETO") model = AutoModelForSequenceClassification.from_pretrained("tr3cks/SentimentAnalysis_BETO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from tr3cks/SentimentAnalysis_BETO: direct link, hf CLI and curl.
- Browser
- Download file 520 Bytes
-
https://huggingface.co/tr3cks/SentimentAnalysis_BETO/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://tr3cks/SentimentAnalysis_BETO/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/tr3cks/SentimentAnalysis_BETO/resolve/main/tokenizer_config.json
520 Bytes
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 256, "special_tokens_map_file": "/root/.cache/huggingface/transformers/78141ed1e8dcc5ff370950397ca0d1c5c9da478f54ec14544187d8a93eff1a26.dd8bd9bfd3664b530ea4e645105f557769387b3da9f79bdb55ed556bdd80611d", "name_or_path": "dccuchile/bert-base-spanish-wwm-uncased", "do_basic_tokenize": true, "never_split": null} |