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---
base_model: btaskel/Tifa-DeepsexV2-7b-MGRPO-safetensors
language:
- zh
- en
library_name: transformers
tags:
- incremental-pretraining
- sft
- reinforcement-learning
- roleplay
- cot
- mlx
- mlx-my-repo
license: apache-2.0
---
# KYUNGYONG/Tifa-DeepsexV2-7b-MGRPO-safetensors-4bit
The Model [KYUNGYONG/Tifa-DeepsexV2-7b-MGRPO-safetensors-4bit](https://huggingface.co/KYUNGYONG/Tifa-DeepsexV2-7b-MGRPO-safetensors-4bit) was converted to MLX format from [btaskel/Tifa-DeepsexV2-7b-MGRPO-safetensors](https://huggingface.co/btaskel/Tifa-DeepsexV2-7b-MGRPO-safetensors) using mlx-lm version **0.21.5**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("KYUNGYONG/Tifa-DeepsexV2-7b-MGRPO-safetensors-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)
```
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