File size: 1,580 Bytes
6f6c459 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
---
license: gemma
library_name: transformers
tags:
- mlx
- mlx
- mlx-my-repo
extra_gated_heading: Access CodeGemma on Hugging Face
extra_gated_prompt: To access CodeGemma on Hugging Face, you’re required to review
and agree to Google’s usage license. To do this, please ensure you’re logged-in
to Hugging Face and click below. Requests are processed immediately.
extra_gated_button_content: Acknowledge license
pipeline_tag: text-generation
widget:
- text: '<start_of_turn>user Write a Python function to calculate the nth fibonacci
number.<end_of_turn> <start_of_turn>model
'
inference:
parameters:
max_new_tokens: 200
license_link: https://ai.google.dev/gemma/terms
base_model: mlx-community/codegemma-7b-it-8bit
---
# introvoyz041/codegemma-7b-it-8bit-mlx-4Bit
The Model [introvoyz041/codegemma-7b-it-8bit-mlx-4Bit](https://huggingface.co/introvoyz041/codegemma-7b-it-8bit-mlx-4Bit) was converted to MLX format from [mlx-community/codegemma-7b-it-8bit](https://huggingface.co/mlx-community/codegemma-7b-it-8bit) using mlx-lm version **0.28.3**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("introvoyz041/codegemma-7b-it-8bit-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
```
|