Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use mfidabel/bert-base-multilingual-uncased-sentiment-finetuned-MeIA-AnalisisDeSentimientos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mfidabel/bert-base-multilingual-uncased-sentiment-finetuned-MeIA-AnalisisDeSentimientos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mfidabel/bert-base-multilingual-uncased-sentiment-finetuned-MeIA-AnalisisDeSentimientos")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mfidabel/bert-base-multilingual-uncased-sentiment-finetuned-MeIA-AnalisisDeSentimientos") model = AutoModelForSequenceClassification.from_pretrained("mfidabel/bert-base-multilingual-uncased-sentiment-finetuned-MeIA-AnalisisDeSentimientos") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3 opened over 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#1 opened almost 3 years ago
by
SFconvertbot