Instructions to use Visionboxx/ads with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Visionboxx/ads with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Visionboxx/ads", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from Visionboxx/ads: direct link, hf CLI and curl.
- Browser
- Download file 613 Bytes
-
https://huggingface.co/Visionboxx/ads/resolve/main/README.md
- Command line
-
hf download hf://Visionboxx/ads/README.md
-
curl -L -o README.md https://huggingface.co/Visionboxx/ads/resolve/main/README.md
613 Bytes
metadata
base_model: unsloth/mistral-7b-instruct-v0.3-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
license: apache-2.0
language:
- en
Uploaded finetuned model
- Developed by: Visionboxx
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-instruct-v0.3-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
