File size: 2,067 Bytes
4fa18b7 ea65057 4fa18b7 ba94793 4fa18b7 8125718 4fa18b7 c6423fa 947bf74 c6423fa 21e0c4a 947bf74 c6423fa 4fa18b7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
---
tags:
- merge
- mergekit
- lazymergekit
license: apache-2.0
---
<img src="https://cdn-uploads.huggingface.co/production/uploads/6389d3c61e8755d777902366/-_AiKUEsY3x-N7oY52fdE.jpeg" style="border-radius:2%; width: 66%">
# pandafish-7b
pandafish-7b is an instruct model based on a [Model Stock](https://arxiv.org/abs/2403.19522) merge of the following models (via [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing)):
## 🧩 Configuration
```yaml
models:
- model: mistralai/Mistral-7B-v0.1
- model: mistralai/Mistral-7B-Instruct-v0.2
- model: CultriX/NeuralTrix-bf16
- model: OpenPipe/mistral-ft-optimized-1227
merge_method: model_stock
base_model: mistralai/Mistral-7B-v0.1
dtype: bfloat16
```
## 🏆 Evals
| Model |Average|AGIEval|GPT4All|TruthfulQA|Bigbench|
|---------------------------------------------------------------|------:|------:|---------:|-------:|------:|
|[pandafish-7b](https://huggingface.co/ichigoberry/pandafish-7b) [📄](https://gist.github.com/tosh/dda6a21e568d17a410ca618265f64a28)| 51.99 | **40** | **74.23** | 53.22 | 40.51 |
|[mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) [📄](https://gist.github.com/mlabonne/05d358e17dffdf9eee7c2322380c9da6) | 54.81 | 38.5 | 71.64 | **66.82** | **42.29** |
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "ichigoberry/pandafish-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"])
``` |