Instructions to use bcoding/deepseek-llvm-sft-lora-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bcoding/deepseek-llvm-sft-lora-7B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bcoding/deepseek-llvm-sft-lora-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from bcoding/deepseek-llvm-sft-lora-7B: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/bcoding/deepseek-llvm-sft-lora-7B/resolve/main/tokenizer.json
- Command line
-
hf download hf://bcoding/deepseek-llvm-sft-lora-7B/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bcoding/deepseek-llvm-sft-lora-7B/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 1e9e1dbcef420dbdfded58721d0c06d1edfa3339be204def0b132a773f7b72f8
- Size of remote file:
- 11.4 MB
- SHA256:
- 7dd428a75dd3f5fee680bc99c4cc951a78a8699f1493b8a4127c0bac2743389b
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