Zero-Shot Classification
Transformers
Safetensors
English
qwen3_5
feature-extraction
ollaya
sura
decision
classification
distillation
Instructions to use ollaya-dev/sura-0.8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ollaya-dev/sura-0.8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="ollaya-dev/sura-0.8b")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("ollaya-dev/sura-0.8b") model = AutoModel.from_pretrained("ollaya-dev/sura-0.8b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download joint_config.json from ollaya-dev/sura-0.8b: direct link, hf CLI and curl.
- Browser
- Download file 248 Bytes
-
https://huggingface.co/ollaya-dev/sura-0.8b/resolve/main/joint_config.json
- Command line
-
hf download hf://ollaya-dev/sura-0.8b/joint_config.json
-
curl -L -o joint_config.json https://huggingface.co/ollaya-dev/sura-0.8b/resolve/main/joint_config.json
248 Bytes
| { | |
| "version": 3, | |
| "template": "joint-question-inline-readout-v1", | |
| "marker": "<|fim_suffix|>", | |
| "readout_offset": 0, | |
| "max_questions": null, | |
| "max_length": null, | |
| "usage": "nonpadding_joint_sequence_including_template_and_image_positions" | |
| } | |