Feature Extraction
Transformers
Safetensors
qwen3
Generated from Trainer
sft
trl
unsloth
text-embeddings-inference
Instructions to use zerostratos/qwen_prm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zerostratos/qwen_prm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zerostratos/qwen_prm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("zerostratos/qwen_prm") model = AutoModel.from_pretrained("zerostratos/qwen_prm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from zerostratos/qwen_prm: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/zerostratos/qwen_prm/resolve/main/tokenizer.json
- Command line
-
hf download hf://zerostratos/qwen_prm/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/zerostratos/qwen_prm/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.