Instructions to use ThorBaller/lora_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThorBaller/lora_model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="ThorBaller/lora_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ThorBaller/lora_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from ThorBaller/lora_model: direct link, hf CLI and curl.
- Browser
- Download file 609 Bytes
-
https://huggingface.co/ThorBaller/lora_model/resolve/main/README.md
- Command line
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hf download hf://ThorBaller/lora_model/README.md
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curl -L -o README.md https://huggingface.co/ThorBaller/lora_model/resolve/main/README.md
609 Bytes
metadata
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
base_model: unsloth/llama-3-8b-bnb-4bit
pipeline_tag: question-answering
Uploaded model
- Developed by: ThorBaller
- License: apache-2.0
- Finetuned from model : unsloth/llama-3-8b-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
