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
Download checkpoint-105/optimizer.pt from jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42: direct link, hf CLI and curl.
- Browser
- Download file 162 MB
-
https://huggingface.co/jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42/resolve/04ac41ea0788f5a61a8a46d0d3fc2b68ae3edda8/checkpoint-105/optimizer.pt
- Command line
-
hf download hf://jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42@04ac41ea0788f5a61a8a46d0d3fc2b68ae3edda8/checkpoint-105/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42/resolve/04ac41ea0788f5a61a8a46d0d3fc2b68ae3edda8/checkpoint-105/optimizer.pt
162 MB
- Xet hash:
- aea9f17cc707506213267e7e788b4b08a5a9fc8d725ae2c610bbde1224473e4d
- Size of remote file:
- 162 MB
- SHA256:
- 275ccb1e6713955ad31ec087844d2ff34cf385a035f082c61d292bb2669c8d97
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