Text Classification
Transformers
Safetensors
Spanish
bert
machine-learning
educational-example
text-embeddings-inference
Instructions to use WalterWi/transformers_clas_texto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WalterWi/transformers_clas_texto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="WalterWi/transformers_clas_texto")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("WalterWi/transformers_clas_texto") model = AutoModelForSequenceClassification.from_pretrained("WalterWi/transformers_clas_texto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 179 Bytes
f343795 | 1 2 3 4 5 6 7 8 | {
"cls_token": "[CLS]",
"model_max_length": 32,
"pad_token": "[PAD]",
"sep_token": "[SEP]",
"tokenizer_class": "PreTrainedTokenizerFast",
"unk_token": "[UNK]"
} |