KoQwen_72B_v5.0 / README.md
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---
language:
- ko
- en
license: cc-by-nc-4.0
library_name: transformers
tags:
- mergekit
- merge
base_model:
- Nexusflow/Athene-V2-Chat
- Nexusflow/Athene-V2-Agent
- anthracite-org/magnum-v4-72b
- Qwen/Qwen2.5-72B-Instruct
---
# spow12/MK_Nemo_12B
### Model Description
<!-- Provide a longer summary of what this model is. -->
This model is a Supervised fine-tuned version of [Qwen/Qwen2.5-72B-Instruct](https://huggingface.co./Qwen/Qwen2.5-72B-Instruct) with DeepSpeed and trl for korean.
Merge methods.
```yaml
merge_method: model_stock
name: ChatWaifu_72B_V2.4
models:
- model: Nexusflow/Athene-V2-Chat
- model: Nexusflow/Athene-V2-Agent
- model: Qwen/Qwen2.5-72B-Instruct_instruction_tunned(private)
- model: anthracite-org/magnum-v4-72b
base_model: Qwen/Qwen2.5-72B-Instruct
dtype: bfloat16
tokenizer_source: base
```
### Trained Data
- Trained with public, private data (about 500K)
### Usage
```python
from transformers import TextStreamer, pipeline, AutoTokenizer, AutoModelForCausalLM
model_id = 'spow12/KoQwen_72B_v5.0'
tokenizer = AutoTokenizer.from_pretrained(model_id)
# %%
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
attn_implementation="flash_attention_2", #Optional
device_map='auto',
)
model.eval()
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, device_map='auto')
generation_configs = dict(
max_new_tokens=2048,
num_return_sequences=1,
temperature=0.75,
# repetition_penalty=1.1,
do_sample=True,
top_k=20,
top_p=0.9,
min_p=0.1,
eos_token_id=tokenizer.eos_token_id,
pad_token_id=tokenizer.eos_token_id,
streamer = TextStreamer(tokenizer) # Optional, if you want to use streamer, you have to set num_beams=1
)
sys_message = """당신은 μΉœμ ˆν•œ μ±—λ΄‡μœΌλ‘œμ„œ μƒλŒ€λ°©μ˜ μš”μ²­μ— μ΅œλŒ€ν•œ μžμ„Έν•˜κ³  μΉœμ ˆν•˜κ²Œ λ‹΅ν•΄μ•Όν•©λ‹ˆλ‹€.
μ‚¬μš©μžκ°€ μ œκ³΅ν•˜λŠ” 정보λ₯Ό μ„Έμ‹¬ν•˜κ²Œ λΆ„μ„ν•˜μ—¬ μ‚¬μš©μžμ˜ μ˜λ„λ₯Ό μ‹ μ†ν•˜κ²Œ νŒŒμ•…ν•˜κ³  그에 따라 닡변을 μƒμ„±ν•΄μ•Όν•©λ‹ˆλ‹€.
항상 맀우 μžμ—°μŠ€λŸ¬μš΄ ν•œκ΅­μ–΄λ‘œ μ‘λ‹΅ν•˜μ„Έμš”."""
message = [
{
'role': "system",
'content': sys_message
},
{
'role': 'user',
'content': "ν˜„μž¬μ˜ κ²½μ œμƒν™©μ— λŒ€ν•΄ μ–΄λ–»κ²Œ 생각해?."
}
]
conversation = pipe(message, **generation_configs)
conversation[-1]
```