Text Classification
Transformers
Safetensors
decision-model
classification
julia
open-jev
head-finetune
low-resource
Instructions to use SHSLab/Qyvos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHSLab/Qyvos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SHSLab/Qyvos")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SHSLab/Qyvos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 296 Bytes
31f7037 | 1 2 3 4 5 6 7 8 9 10 11 | {
"format_version": 1,
"architecture": "JuliaDecisionModel",
"julia_config_file": "julia_config.json",
"encoder_config_file": "encoder/config.json",
"weights_file": "model.safetensors",
"tokenizer_directory": "tokenizer",
"name": "Qyvos",
"base_model": "SupersonicLabs/Julia-1"
}
|