Instructions to use Qwen/Qwen3Guard-Stream-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen3Guard-Stream-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Qwen/Qwen3Guard-Stream-4B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3Guard-Stream-4B", trust_remote_code=True) model = AutoModel.from_pretrained("Qwen/Qwen3Guard-Stream-4B", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf5792f5840c151853afb7a17edee433e312b18f6ce37ff77200a92843e741ef
- Size of remote file:
- 4.97 GB
- SHA256:
- f14725577bd45f130101f054cb52142572447631812ebabfc06808cf23613577
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.