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/tokenizer.json from jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42/resolve/04ac41ea0788f5a61a8a46d0d3fc2b68ae3edda8/checkpoint-105/tokenizer.json
- Command line
-
hf download hf://jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42@04ac41ea0788f5a61a8a46d0d3fc2b68ae3edda8/checkpoint-105/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/jeqcho/persona_7b_to_7b-qwen25-7b-pangolin-random_10k-seed42/resolve/04ac41ea0788f5a61a8a46d0d3fc2b68ae3edda8/checkpoint-105/tokenizer.json
11.4 MB
- Xet hash:
- 2e96dd4ae1d2df772ea3bbc942468b6f624624d437352f82360c528a3910b730
- Size of remote file:
- 11.4 MB
- SHA256:
- fab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a
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