Instructions to use bumblebee-testing/tiny-random-Qwen3Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bumblebee-testing/tiny-random-Qwen3Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bumblebee-testing/tiny-random-Qwen3Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bumblebee-testing/tiny-random-Qwen3Model") model = AutoModel.from_pretrained("bumblebee-testing/tiny-random-Qwen3Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from bumblebee-testing/tiny-random-Qwen3Model: direct link, hf CLI and curl.
- Browser
- Download file 558 kB
-
https://huggingface.co/bumblebee-testing/tiny-random-Qwen3Model/resolve/main/model.safetensors
- Command line
-
hf download hf://bumblebee-testing/tiny-random-Qwen3Model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/bumblebee-testing/tiny-random-Qwen3Model/resolve/main/model.safetensors
558 kB
- Xet hash:
- 14dcd111ce26f221f52096dfc1ed7b2ec0615c64efacc3b8c52d2b4a7937b8d7
- Size of remote file:
- 558 kB
- SHA256:
- b5f3ca0dbd55d742312956713f350272f78c3b4adb0ea2beec542da30479eafe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.