Text Classification
Transformers
Safetensors
xlm-roberta
computer-use
browser-agents
agent-safety
human-in-the-loop
multilingual
text-embeddings-inference
Instructions to use decosaai/decosa-commit-detector-xlmr-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use decosaai/decosa-commit-detector-xlmr-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="decosaai/decosa-commit-detector-xlmr-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("decosaai/decosa-commit-detector-xlmr-large") model = AutoModelForSequenceClassification.from_pretrained("decosaai/decosa-commit-detector-xlmr-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decosa_commit.json from decosaai/decosa-commit-detector-xlmr-large: direct link, hf CLI and curl.
- Browser
- Download file 177 Bytes
-
https://huggingface.co/decosaai/decosa-commit-detector-xlmr-large/resolve/main/decosa_commit.json
- Command line
-
hf download hf://decosaai/decosa-commit-detector-xlmr-large/decosa_commit.json
-
curl -L -o decosa_commit.json https://huggingface.co/decosaai/decosa-commit-detector-xlmr-large/resolve/main/decosa_commit.json
177 Bytes
| {"kinds": ["none", "pay", "delete", "send", "publish", "submit", "security"], "maxlen": 160, "safety_threshold_pnone": 0.7000000000000001, "text_format": "see infer.py text_of"} |