---
base_model:
- cognitivecomputations/dolphin-2.9.1-llama-3-70b
library_name: transformers
tags:
- mergekit
- merge
language:
- en
datasets:
- cognitivecomputations/Dolphin-2.9
- teknium/OpenHermes-2.5
- m-a-p/CodeFeedback-Filtered-Instruction
- cognitivecomputations/dolphin-coder
- cognitivecomputations/samantha-data
- HuggingFaceH4/ultrachat_200k
- microsoft/orca-math-word-problems-200k
- abacusai/SystemChat-1.1
- Locutusque/function-calling-chatml
- internlm/Agent-FLAN
---

![image/jpeg](https://i.postimg.cc/wMwjKj19/mega-dolphin.png)

# merge

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the passthrough merge method.

### Models Merged

The following models were included in the merge:
* [cognitivecomputations/dolphin-2.9.1-llama-3-70b](https://huggingface.co/cognitivecomputations/dolphin-2.9.1-llama-3-70b)
* [cognitivecomputations/dolphin-2.9.1-llama-3-70b](https://huggingface.co/cognitivecomputations/dolphin-2.9.1-llama-3-70b)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
- sources:
  - layer_range: [0, 20]
    model: cognitivecomputations/dolphin-2.9.1-llama-3-70b
- sources:
  - layer_range: [10, 30]
    model: cognitivecomputations/dolphin-2.9.1-llama-3-70b
- sources:
  - layer_range: [20, 40]
    model: cognitivecomputations/dolphin-2.9.1-llama-3-70b
- sources:
  - layer_range: [30, 50]
    model: cognitivecomputations/dolphin-2.9.1-llama-3-70b
- sources:
  - layer_range: [40, 60]
    model: cognitivecomputations/dolphin-2.9.1-llama-3-70b
- sources:
  - layer_range: [50, 70]
    model: cognitivecomputations/dolphin-2.9.1-llama-3-70b
- sources:
  - layer_range: [60, 80]
    model: cognitivecomputations/dolphin-2.9.1-llama-3-70b
merge_method: passthrough
dtype: float16
```

This model uses ChatML prompt template format.

example:

```
<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "DarqueDante/LLama-3-Dolphin-2.9.1-120b"
messages = [{"role": "user", "content": "Who is Andrej Karpathy?"}]

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"])
```