Text Classification
Transformers
Safetensors
English
nli
cross-encoder
qwen3.5
reranker
image-text-to-text
Instructions to use ldov/openjevv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ldov/openjevv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ldov/openjevv")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ldov/openjevv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download results/minecraft_sim.json from ldov/openjevv: direct link, hf CLI and curl.
- Browser
- Download file 2.92 MB
-
https://huggingface.co/ldov/openjevv/resolve/main/results/minecraft_sim.json
- Command line
-
hf download hf://ldov/openjevv/results/minecraft_sim.json
-
curl -L -o minecraft_sim.json https://huggingface.co/ldov/openjevv/resolve/main/results/minecraft_sim.json
2.92 MB
File too large to display, you can check the raw version instead.