Instructions to use jayavibhav/qwen3-4b-base-lora-checkpoint-50s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayavibhav/qwen3-4b-base-lora-checkpoint-50s with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jayavibhav/qwen3-4b-base-lora-checkpoint-50s", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe35a38c0f237cdbe14a81102e445e35d2b310999909420de9d964a69b172291
- Size of remote file:
- 11.8 MB
- SHA256:
- 9075c72515c8c1cd7724d5e8473aa9b093a705d192022e6ff86038c34362c10a
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