Text Classification
Transformers
Safetensors
English
nli
cross-encoder
qwen3.5
reranker
image-text-to-text
Instructions to use AlexWortega/openjev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexWortega/openjev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AlexWortega/openjev")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AlexWortega/openjev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Use pairwise batch for one or two hypotheses
Verified signatureAvoid shared-prefix prefill and cache branching for small option sets. Keep shared-prefix inference for three or more hypotheses and test the routing.c959f4d -
Share Qwen3.5 prefix cache across NLI hypotheses
Verified signatureAdd batched cached continuation for hypotheses sharing one premise. Qwen3.5 recurrent linear-attention state and full-attention KV cache are branched per hypothesis after one prefix prefill. Rerank uses the new path; tiny hybrid-model tests compare against independent pair inference and check branch isolation.e93f6db