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---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
- teknium/OpenHermes-2.5-Mistral-7B
base_model:
- cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
- teknium/OpenHermes-2.5-Mistral-7B
---
# Combined-Test-14B-OpenHermes-2.5-Mistral-7B-and-dolphin-2.6-mistral-7b-dpo-laser
Combined-Test-14B-OpenHermes-2.5-Mistral-7B-and-dolphin-2.6-mistral-7b-dpo-laser is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser)
* [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
layer_range: [0, 32]
- sources:
- model: teknium/OpenHermes-2.5-Mistral-7B
layer_range: [0, 32]
merge_method: passthrough
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mattshumer/Combined-Test-14B-OpenHermes-2.5-Mistral-7B-and-dolphin-2.6-mistral-7b-dpo-laser"
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"])
``` |