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
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Download README.md from bcoding/deepseek_7b_llvm_sft_lora_2: direct link, hf CLI and curl.
- Browser
- Download file 593 Bytes
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https://huggingface.co/bcoding/deepseek_7b_llvm_sft_lora_2/resolve/main/README.md
- Command line
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hf download hf://bcoding/deepseek_7b_llvm_sft_lora_2/README.md
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curl -L -o README.md https://huggingface.co/bcoding/deepseek_7b_llvm_sft_lora_2/resolve/main/README.md
593 Bytes
metadata
base_model: unsloth/DeepSeek-R1-Distill-Qwen-7B-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
license: apache-2.0
language:
- en
Uploaded model
- Developed by: bcoding
- License: apache-2.0
- Finetuned from model : unsloth/DeepSeek-R1-Distill-Qwen-7B-unsloth-bnb-4bit
This qwen2 model was trained 2x faster with Unsloth
