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
File size: 520 Bytes
2aa2f4e | 1 | {"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} |