README.md

metadata

language:
  - en
thumbnail: https://your-thumbnail-url.com/image.png
tags:
  - quantization
  - gemma
  - 4bit
  - causal-lm
license: apache-2.0
datasets:
  - your-dataset-name
metrics:
  - perplexity
base_model: google/gemma-2b

Gemma 2B Quantized 4-bit

This repository contains a 4-bit quantized version of the Gemma 2B model.

Files

• config.json: Model configuration.
• generation_config.json: Generation parameters.
• model.safetensors: Quantized model weights.
• special_tokens_map.json: Special tokens mapping.
• tokenizer_config.json: Tokenizer configuration.
• tokenizer.json: Tokenizer vocabulary.

Usage

You can load this model using the Hugging Face Transformers library:

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("your-username/gemma-2b-quantized-4bit")
tokenizer = AutoTokenizer.from_pretrained("your-username/gemma-2b-quantized-4bit")

License

This model is licensed under the Apache 2.0 License. See LICENSE for details.

Credits

• Original model: Gemma 2B
• Quantization: 4-bit

```text:LICENSE
                                 Apache License
                           Version 2.0, January 2004
                        http://www.apache.org/licenses/

   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.

# System files
.DS_Store
Thumbs.db

# Python cache
__pycache__/
*.pyc

# Jupyter Notebook checkpoints
.ipynb_checkpoints/

# VSCode settings
.vscode/

# Large files (remove if you want to include model weights in git)
*.safetensors

---

What to do next:

• Fill in the placeholders in README.md (thumbnail, datasets, etc.).
• If you want to include model.safetensors in your GitHub repo, remove *.safetensors from .gitignore.
• Initialize git, commit, and push to GitHub.
• You’re now ready to upload to Hugging Face!

Let me know if you want any further customization or help with the git/Hugging Face steps!