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---
tags:
- merge
- mergekit
- lazymergekit
- DiscoResearch/DiscoLM_German_7b_v1
- DRXD1000/Phoenix
- OpenPipe/mistral-ft-optimized-1227
base_model:
- DiscoResearch/DiscoLM_German_7b_v1
- DRXD1000/Phoenix
- OpenPipe/mistral-ft-optimized-1227
license: apache-2.0
language:
- de
---
# DiscoPhoenix-7B
DiscoPhoenix-7B is a dpo tuned merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [DiscoResearch/DiscoLM_German_7b_v1](https://huggingface.co/DiscoResearch/DiscoLM_German_7b_v1)
* [DRXD1000/Phoenix](https://huggingface.co/DRXD1000/Phoenix)
* [OpenPipe/mistral-ft-optimized-1227](https://huggingface.co/OpenPipe/mistral-ft-optimized-1227)
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
# No parameters necessary for base model
- model: DiscoResearch/DiscoLM_German_7b_v1
parameters:
density: 0.6
weight: 0.3
- model: DRXD1000/Phoenix
parameters:
density: 0.6
weight: 0.3
- model: OpenPipe/mistral-ft-optimized-1227
parameters:
density: 0.6
weight: 0.4
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
int8_mask: true
dtype: bfloat16
```
## mt-bench-de results
```json
{
"first_turn": 7.3354430379746836,
"second_turn": 6.65,
"categories": {
"writing": 8.7,
"roleplay": 7.605263157894737,
"reasoning": 5.75,
"math": 3.3,
"coding": 5.3,
"extraction": 7.55,
"stem": 8.4,
"humanities": 9.35
},
"average": 6.9927215189873415
}
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mayflowergmbh/DiscoPhoenix-7B"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
``` |