Text Classification
Transformers
Safetensors
Spanish
roberta
nli
spanish
causal
esnlir
active-learning
text-embeddings-inference
Instructions to use Flaglab/ESNLIR-AL-BERTIN-LER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Flaglab/ESNLIR-AL-BERTIN-LER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Flaglab/ESNLIR-AL-BERTIN-LER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Flaglab/ESNLIR-AL-BERTIN-LER") model = AutoModelForSequenceClassification.from_pretrained("Flaglab/ESNLIR-AL-BERTIN-LER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Flaglab/ESNLIR-AL-BERTIN-LER: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/Flaglab/ESNLIR-AL-BERTIN-LER/resolve/main/training_args.bin
- Command line
-
hf download hf://Flaglab/ESNLIR-AL-BERTIN-LER/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Flaglab/ESNLIR-AL-BERTIN-LER/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- 8c6ca7dc2076b14a36f6cfd30a270bb7f6595ba56d02d8fa7eb89058699e68a9
- Size of remote file:
- 5.91 kB
- SHA256:
- 545035bf99eef1c4386bf9d050ef1cf21676cc8d488795f83fa42451fb0c6009
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