Text Classification
Transformers
PyTorch
Safetensors
Spanish
roberta
sagemaker
bertin
TextClassification
SentimentAnalysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use edumunozsala/bertin_base_sentiment_analysis_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edumunozsala/bertin_base_sentiment_analysis_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="edumunozsala/bertin_base_sentiment_analysis_es")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("edumunozsala/bertin_base_sentiment_analysis_es") model = AutoModelForSequenceClassification.from_pretrained("edumunozsala/bertin_base_sentiment_analysis_es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from edumunozsala/bertin_base_sentiment_analysis_es: direct link, hf CLI and curl.
- Browser
- Download file 239 Bytes
-
https://huggingface.co/edumunozsala/bertin_base_sentiment_analysis_es/resolve/refs%2Fpr%2F2/special_tokens_map.json
- Command line
-
hf download hf://edumunozsala/bertin_base_sentiment_analysis_es@refs/pr/2/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/edumunozsala/bertin_base_sentiment_analysis_es/resolve/refs%2Fpr%2F2/special_tokens_map.json
239 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}} |