Text Ranking
Transformers
Safetensors
multilingual
qwen3
text-generation
reranker
nvfp4
fp4
compressed-tensors
llm-compressor
vllm
Eval Results (legacy)
8-bit precision
Instructions to use KoliaNik/Qwen3-Reranker-4B-NVFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoliaNik/Qwen3-Reranker-4B-NVFP4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("KoliaNik/Qwen3-Reranker-4B-NVFP4") model = AutoModelForCausalLM.from_pretrained("KoliaNik/Qwen3-Reranker-4B-NVFP4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from KoliaNik/Qwen3-Reranker-4B-NVFP4: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/KoliaNik/Qwen3-Reranker-4B-NVFP4/resolve/main/tokenizer.json
- Command line
-
hf download hf://KoliaNik/Qwen3-Reranker-4B-NVFP4/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/KoliaNik/Qwen3-Reranker-4B-NVFP4/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 047fb6fb74dafdddc051eb170116838d7800960aa1a7b8be327a7d3c1abc4de7
- Size of remote file:
- 11.4 MB
- SHA256:
- b064181fd20c7d19d5613f061552279d7dcbb8210ffde80386e2a9a6ddf996e7
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