Instructions to use Avinier/ssllm-v2.7_4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Avinier/ssllm-v2.7_4bit with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Avinier/ssllm-v2.7_4bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from Avinier/ssllm-v2.7_4bit: direct link, hf CLI and curl.
- Browser
- Download file 592 Bytes
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https://huggingface.co/Avinier/ssllm-v2.7_4bit/resolve/main/README.md
- Command line
-
hf download hf://Avinier/ssllm-v2.7_4bit/README.md
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curl -L -o README.md https://huggingface.co/Avinier/ssllm-v2.7_4bit/resolve/main/README.md
592 Bytes
metadata
base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
Uploaded model
- Developed by: Avinier
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-Instruct-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
