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---
tags:
- merge
- mergekit
- lazymergekit
- rhysjones/phi-2-orange
- cognitivecomputations/dolphin-2_6-phi-2
- Microsoft/Phi-2
base_model:
- rhysjones/phi-2-orange
- cognitivecomputations/dolphin-2_6-phi-2
license: mit
---
# Phiter
<img src="https://cdn-uploads.huggingface.co/production/uploads/6493317e9621f988db6c469c/ZjXk8XIDt00E2n6j4brQW.png" alt="Phiter Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
Phiter is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [rhysjones/phi-2-orange](https://huggingface.co/rhysjones/phi-2-orange)
* [cognitivecomputations/dolphin-2_6-phi-2](https://huggingface.co/cognitivecomputations/dolphin-2_6-phi-2)
Thanks to the great [Maxime Labonne](https://huggingface.co/mlabonne) we have evaluation results on [YALL](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).
The model tops all other phi-2 finetunes on the leaderboard, even most MoE implementations like Phixtral(Date: 27th February 2024)
License: MIT
This model wouldn't have been possible without the support of:
[Maxime Labonne](https://huggingface.co/mlabonne) - he helped me troubleshoot the merge process
[brittlewis12](https://huggingface.co/brittlewis12) - helped me troubleshooting the creation of GGUF files
<!-- prompt-template start -->
## Prompt template: ChatML
```
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
```
<!-- prompt-template end -->
GGUF: [Phiter-GGUF](https://huggingface.co/Venkman42/Phiter-GGUF/)
## 🧩 Configuration
```yaml
models:
- model: mixedbread-ai/phi-2
# no parameters necessary for base model
- model: rhysjones/phi-2-orange
parameters:
density: 0.5
weight: 0.5
- model: cognitivecomputations/dolphin-2_6-phi-2
parameters:
density: 0.5
weight: 0.3
merge_method: ties
base_model: mixedbread-ai/phi-2
parameters:
normalize: true
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Venkman42/Phiter"
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"])
``` |