Downloads · 30 days
5
36% of all-time downloads
unsloth_-_codegemma-2b-8bits
RichardErkhov/unsloth_-_codegemma-2b-8bits
unsloth_-_codegemma-2b-8bits 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.
All-time downloads
14
Public
Parameters
2.5B
3.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors3 GB · 99%
Parameter types
How the weights are stored.
I82B · 79%
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
codegemma-2b - bnb 8bits
- Model creator: https://huggingface.co/unsloth/
- Original model: https://huggingface.co/unsloth/codegemma-2b/
Original model description:
language:
- en library_name: transformers license: apache-2.0 tags:
- unsloth
- transformers
- gemma
- bnb
Finetune Mistral, Gemma, Llama 2-5x faster with 70% less memory via Unsloth!
We have a Google Colab Tesla T4 notebook for CodeGemma 7b here: https://colab.research.google.com/drive/19lwcRk_ZQ_ZtX-qzFP3qZBBHZNcMD1hh?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"/>
✨ 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% less |
| DPO - Zephyr | ▶️ Start on Colab | 1.9x faster | 19% less |
- This conversational notebook is useful for ShareGPT ChatML / Vicuna templates.
- This text completion notebook is for raw text. This DPO notebook replicates Zephyr.
- * Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.
- Type
- gemma
- Created
- Oct 11, 2024
- Updated
- Oct 11, 2024