Text Classification
Transformers
Safetensors
English
Chinese
qwen3
text-generation
zen
zen-reranker
zenlm
hanzo
reranker
retrieval
text-embeddings-inference
Instructions to use zenlm/zen-reranker-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen-reranker-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zenlm/zen-reranker-4B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zenlm/zen-reranker-4B") model = AutoModelForCausalLM.from_pretrained("zenlm/zen-reranker-4B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 325 Bytes
7bb9aba | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"__version__": {
"pytorch": "2.10.0+cu128",
"sentence_transformers": "5.4.0"
},
"activation_fn": "torch.nn.modules.linear.Identity",
"default_prompt_name": "query",
"model_type": "CrossEncoder",
"prompts": {
"query": "Given a web search query, retrieve relevant passages that answer the query"
}
} |