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RichardErkhov/unsloth_-_gemma-1.1-2b-it-awq
unsloth_-_gemma-1.1-2b-it-awq is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
2
9% of all-time downloads
All-time downloads
23
Public
Parameters
2.5B
2.1 GB on disk
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Public
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.safetensors2.1 GB · 98%
How the weights are stored.
I322B · 79%
From the Hugging Face model README
Quantization made by Richard Erkhov.
gemma-1.1-2b-it - AWQ
language:
We have a Google Colab Tesla T4 notebook for Gemma 2b here: https://colab.research.google.com/drive/15gGm7x_jTm017_Ic8e317tdIpDG53Mtu?usp=sharing
<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/Discord%20button.png" width="200"/> <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/buy%20me%20a%20coffee%20button.png" width="200"/> <img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>
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% less |
| DPO - Zephyr | ▶️ Start on Colab | 1.9x faster | 19% less |