Instructions to use SvalTek/MN-CharThink-Base-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SvalTek/MN-CharThink-Base-LoRA with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("SvalTek/MN-CharThink-Base-LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from SvalTek/MN-CharThink-Base-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/SvalTek/MN-CharThink-Base-LoRA/resolve/main/tokenizer.json
- Command line
-
hf download hf://SvalTek/MN-CharThink-Base-LoRA/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SvalTek/MN-CharThink-Base-LoRA/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 63e4b53436d4cf5c287f39c50cfef04eacfcfde06a89f349f86f96b3e8924770
- Size of remote file:
- 17.1 MB
- SHA256:
- 5d7cdf4abdcf2582c9f4d0b852fcbacd98f42dc86c58f8f46b4bb75e03274496
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