Instructions to use bcoding/deepseek_7b_llvm_sft_lora_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bcoding/deepseek_7b_llvm_sft_lora_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bcoding/deepseek_7b_llvm_sft_lora_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from bcoding/deepseek_7b_llvm_sft_lora_2: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/bcoding/deepseek_7b_llvm_sft_lora_2/resolve/main/tokenizer.json
- Command line
-
hf download hf://bcoding/deepseek_7b_llvm_sft_lora_2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bcoding/deepseek_7b_llvm_sft_lora_2/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 82fa60658ea1463674a135e3ac85d2dc0bfca9174f924b9b7f2cafc33bf4c32c
- Size of remote file:
- 11.4 MB
- SHA256:
- e20ddafc659ba90242154b55275402edeca0715e5dbb30f56815a4ce081f4893
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