---
title: codegemma-7b-pytorch
canonical_url: "https://www.modelscope.cn/models/google/codegemma-7b-pytorch"
md_url: "https://www.modelscope.cn/models/google/codegemma-7b-pytorch.md"
repository: google/codegemma-7b-pytorch
last_updated: 2025-04-22
license: gemma
pipeline_tag: text-generation
tasks:
  - text-generation
library_name:
  - pytorch
frameworks:
  - pytorch
downloads: 420
stars: 0
tags:
  - pytorch
---

# codegemma-7b-pytorch

> codegemma-7b-pytorch - google 在 ModelScope 开源的模型。CodeGemma Model Card

google/codegemma-7b-pytorch 是 ModelScope 魔搭社区上的text-generation模型，采用 gemma 许可。

- **Repository**: google/codegemma-7b-pytorch
- **License**: gemma
- **Tasks**: text-generation
- **Tags**: pytorch
- **Downloads**: 420
- **Stars**: 0
- **Last updated**: 2025-04-22

Source: https://www.modelscope.cn/models/google/codegemma-7b-pytorch

---

# CodeGemma Model Card

> [!IMPORTANT]
>
> This repository corresponds to the CodeGemma 7B checkpoint for use with [Gemma PyTorch](https://github.com/google/gemma_pytorch). If you're looking for the `transformers` implementation, or more detailed model card, visit https://huggingface.co/google/codegemma-7b.

**Model Page**: [CodeGemma](https://ai.google.dev/gemma/docs/codegemma)

**Resources and Technical Documentation**:

* [Technical Report](https://goo.gle/codegemma)
* [Responsible Generative AI Toolkit](https://ai.google.dev/responsible)

**Terms of Use**: [Terms](https://www.kaggle.com/models/google/codegemma/license/consent/verify/huggingface?returnModelRepoId=google/codegemma-7b-pytorch)

**Authors**: Google

# Sample Usage

```python
from gemma.config import GemmaConfig, get_config_for_7b, get_config_for_2b
from gemma.model import GemmaForCausalLM
from gemma.tokenizer import Tokenizer
import contextlib
import os
import torch

VARIANT = "7b" 
MACHINE_TYPE = "cpu" 
weights_dir = 'codegemma-7b-pytorch' 

@contextlib.contextmanager
def _set_default_tensor_type(dtype: torch.dtype):
  """Sets the default torch dtype to the given dtype."""
  torch.set_default_dtype(dtype)
  yield
  torch.set_default_dtype(torch.float)

model_config = get_config_for_2b() if "2b" in VARIANT else get_config_for_7b()
model_config.tokenizer = os.path.join(weights_dir, "tokenizer.model")

device = torch.device(MACHINE_TYPE)
with _set_default_tensor_type(model_config.get_dtype()):
  model = GemmaForCausalLM(model_config)
  ckpt_path = os.path.join(weights_dir, f'codegemma-{VARIANT}.pt')
  model.load_weights(ckpt_path)
  model = model.to(device).eval()

FIM_PROMPT = """<|fim_prefix|>import <|fim_suffix|>if __name__ == "__main__":
    sys.exit(0)<|fim_middle|>"""

model.generate(
    FIM_PROMPT,
    device=device,
    output_len=100,
)
```