Instructions to use tapxc3/Qwen2-1.5B-Instruct_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tapxc3/Qwen2-1.5B-Instruct_test with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tapxc3/Qwen2-1.5B-Instruct_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ae7344d94650eaf7bac3c9e0d729c08d5df67a74117352c627f211c26e48156
- Size of remote file:
- 6.33 kB
- SHA256:
- e44adb98b892241717f72f96922cec770ddcab87fca595fb9b441a2edca6dd41
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.