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: 337 Bytes
31f7037 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"format_version": 1,
"architecture": "JuliaDecisionModel",
"weight_dtype": "float32",
"head_layers": 2,
"n_act": 2,
"dropout": 0.1,
"name": "Qyvos",
"base_model": "SupersonicLabs/Julia-1",
"dataset": "ZefanCai/Open-Jev",
"dataset_config": "release-v2-redistributable",
"finetune": "head-only (frozen backbone)"
}
|