Instructions to use firejava/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use firejava/lora_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("firejava/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from firejava/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 589 Bytes
-
https://huggingface.co/firejava/lora_model/resolve/5b2ffbea0992e79f18f6d366ea8526c650691d59/README.md
- Command line
-
hf download hf://firejava/lora_model@5b2ffbea0992e79f18f6d366ea8526c650691d59/README.md
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curl -L -o README.md https://huggingface.co/firejava/lora_model/resolve/5b2ffbea0992e79f18f6d366ea8526c650691d59/README.md
589 Bytes
metadata
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
Uploaded model
- Developed by: firejava
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-v0.3-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
