Instructions to use jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
- Xet hash:
- c5d101ef3305dc9a1e4002c84fdae36e71707c742690d360b3459a9a1776c5f8
- Size of remote file:
- 6.48 kB
- SHA256:
- 009a1fb47eaaa1f311a38b8dbb599b2b8c90abef7e0d94e2bc556ac02b5d320d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.