Text Classification
Transformers
Safetensors
Catalan
roberta
eamt-2026
catalan
valencian
translationese
reward-model
text-embeddings-inference
Instructions to use guerreropaula/ht_mt_classifier_best with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guerreropaula/ht_mt_classifier_best with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="guerreropaula/ht_mt_classifier_best")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("guerreropaula/ht_mt_classifier_best") model = AutoModelForSequenceClassification.from_pretrained("guerreropaula/ht_mt_classifier_best", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download data/val.csv from guerreropaula/ht_mt_classifier_best: direct link, hf CLI and curl.
- Browser
- Download file 2.14 MB
-
https://huggingface.co/guerreropaula/ht_mt_classifier_best/resolve/main/data/val.csv
- Command line
-
hf download hf://guerreropaula/ht_mt_classifier_best/data/val.csv
-
curl -L -o val.csv https://huggingface.co/guerreropaula/ht_mt_classifier_best/resolve/main/data/val.csv
2.14 MB
File too large to display, you can check the raw version instead.