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lora_model
xrusnack/lora_model
lora_model is a machine learning model from xrusnack. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
- Finetuned from model : unsloth/gemma-2-9b-bnb-4bit
Access
Public
Updated Nov 16, 2024
Repo size
255 MB
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Repo makeup
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.safetensors216 MB · 85%
At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Nov 16, 2024
- Updated
- Nov 16, 2024
- SHA
- d07b5aef
Base models
Model card
From the Hugging Face model README
Uploaded model
- Finetuned from model : unsloth/gemma-2-9b-bnb-4bit
This gemma2 model was trained 2x faster with Unsloth and Huggingface's TRL library.
Training
The gpt-4o-mini model was used to summarize 100 of the text examples in this dataset https://huggingface.co/datasets/vojtam/czech_books_descriptions The lora model was trained on these summaries.
Example of Inference:
alpaca_prompt = "### Text: {} ### Summary: {}"
FastLanguageModel.for_inference(model)
inputs = tokenizer(
[
alpaca_prompt.format(
"", # text to summarize
"", # output - leave this blank for generation!
)
], return_tensors = "pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True)
tokenizer.batch_decode(outputs)
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Nov 16, 2024
- Updated
- Nov 16, 2024