Instructions to use llavallava/qwen2.5-7b-instruct-trl-sft-lora-social_debug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llavallava/qwen2.5-7b-instruct-trl-sft-lora-social_debug with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("llavallava/qwen2.5-7b-instruct-trl-sft-lora-social_debug", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f8d5dc3430f301e3334c34268c690e5b8dfdc152b46f525db04e968ddb6379ba
- Size of remote file:
- 11.4 MB
- SHA256:
- ba0c439f7be467bf47d12a7e6f9adc6116201056fc60c67f431c679b7c16afc8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.