Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use selsar/nli-subgroups-target-abroad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selsar/nli-subgroups-target-abroad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="selsar/nli-subgroups-target-abroad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("selsar/nli-subgroups-target-abroad") model = AutoModelForSequenceClassification.from_pretrained("selsar/nli-subgroups-target-abroad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from selsar/nli-subgroups-target-abroad: direct link, hf CLI and curl.
- Browser
- Download file 16.4 MB
-
https://huggingface.co/selsar/nli-subgroups-target-abroad/resolve/main/tokenizer.json
- Command line
-
hf download hf://selsar/nli-subgroups-target-abroad/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/selsar/nli-subgroups-target-abroad/resolve/main/tokenizer.json
16.4 MB
- Xet hash:
- b5dea59d2661762b27f3cfccd0198f5994b44d3a56e29edf25676552695269a1
- Size of remote file:
- 16.4 MB
- SHA256:
- be21b6f938c490bffd7a7bfac7a3322bf5173937b2186bb13c7adb747176e52a
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