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Open Source Model Profile · unsloth

gemma-7b-it

gemma-7b-it is an 8.54B-parameter Gemma text-generation model from unsloth. Its card centers on Unsloth notebooks with ShareGPT ChatML and Vicuna template support.

Publisher
unsloth
Task
text-generation
Model type
gemma
License
apache-2.0
Library
transformers
Publication status
Accepted · not indexed

Model overview

gemma-7b-it is published by unsloth as a Gemma text-generation model. The captured configuration identifies GemmaForCausalLM and Safetensors metadata reports 8,537,680,896 parameters, or about 8.54B. The model card focuses on the Unsloth fine-tuning notebook workflow rather than model-specific training or evaluation detail.

Recorded capabilities

8.54B Gemma Transformers record

Captured configuration records GemmaForCausalLM with model type gemma, about 8.54B parameters, and Transformers support with safetensors and conversational markers.

Unsloth notebook workflow

The model card presents Unsloth fine-tuning notebooks and beginner-oriented Run All workflow with export to GGUF, vLLM, or Hugging Face; speed and memory figures describe Unsloth's method rather than measured results for this weights file.

Chat and completion templates

According to the model card, the conversational notebook covers ShareGPT ChatML and Vicuna templates, alongside separate raw-text completion and Zephyr-replicating DPO notebooks.

Use cases in the source record

  • Conversational text-generation experiments using ShareGPT ChatML or Vicuna-style templates, as documented in the model card.
  • Notebook-based fine-tune exports to GGUF, vLLM, or Hugging Face, following the publisher's documented Unsloth workflow rather than this page's deployment claim.

Limitations and unknowns

  • No evaluation results were extracted from this record.
  • No context-window value was extracted from this record.
  • Provider state is historical snapshot data and should be refreshed before being presented as current.
  • Unsloth speed and memory figures in the card describe the fine-tuning method and are not treated as measured performance for this model.

Source and provenance

Source: unsloth/gemma-7b-it

Captured: Unknown. Processed: 2026-09-07T19:35:00.155936+00:00.

Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth! ✨ Finetune for Free All notebooks are beginner friendly ! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face. Unsloth supports Free Notebooks Performance Memory use Gemma 7b ▶️ Start on Colab 2.4x faster 58% less Mistral 7b ▶️ Start on Colab 2.2x faster 62% less Llama-2 7b ▶️ Start on Colab 2.2x faster 43% less TinyLlama ▶️ Start on Colab 3.9x faster 74% less CodeLlama 34b A100 ▶️ Start on Colab 1.9x faster 27% less Mistral 7b 1xT4 ▶️ Start on Kaggle 5x faster* 62% le…

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