Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use emiliam/distilbert-base-multilingual-cased-finetuned-MeIA-AnalisisDeSentimientos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emiliam/distilbert-base-multilingual-cased-finetuned-MeIA-AnalisisDeSentimientos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="emiliam/distilbert-base-multilingual-cased-finetuned-MeIA-AnalisisDeSentimientos")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("emiliam/distilbert-base-multilingual-cased-finetuned-MeIA-AnalisisDeSentimientos") model = AutoModelForSequenceClassification.from_pretrained("emiliam/distilbert-base-multilingual-cased-finetuned-MeIA-AnalisisDeSentimientos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 023078125ac52816fb24de22d8e906672cbd23ecbe9239b4c575bf837fec3b01
- Size of remote file:
- 3.71 kB
- SHA256:
- 9179568dbda3f81e37ac73c88717d189b2cbb72ff15d923c19058ad38bff0fdb
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