Instructions to use Asssmaaaa/Qwen3VL_ft2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Asssmaaaa/Qwen3VL_ft2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Asssmaaaa/Qwen3VL_ft2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Asssmaaaa/Qwen3VL_ft2: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/Asssmaaaa/Qwen3VL_ft2/resolve/main/training_args.bin
- Command line
-
hf download hf://Asssmaaaa/Qwen3VL_ft2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Asssmaaaa/Qwen3VL_ft2/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- a74bbd474ddca77e41d3107f7480b46de683df166c70a12b658f78ed46e08e64
- Size of remote file:
- 5.78 kB
- SHA256:
- 30f04116db96d2f7538c292ba5ba92a26da7a43c9724f8b64e4c9747978ae3fd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.