Instructions to use nikunjbjj/jd-resume-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nikunjbjj/jd-resume-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nikunjbjj/jd-resume-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nikunjbjj/jd-resume-model") model = AutoModelForSequenceClassification.from_pretrained("nikunjbjj/jd-resume-model") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Sentiment Analysis in Spanish
beto-sentiment-analysis
Repository: https://github.com/finiteautomata/pysentimiento/
Model trained with TASS 2020 corpus (around ~5k tweets) of several dialects of Spanish. Base model is BETO, a BERT model trained in Spanish.
Uses POS, NEG, NEU labels.
Coming soon: a brief paper describing the model and training.
Enjoy! 🤗
- Downloads last month
- 10