File size: 2,088 Bytes
e50396a |
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 |
---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- MediaTek-Research/Breeze-7B-Instruct-v0_1
- Azure99/blossom-v4-mistral-7b
base_model:
- MediaTek-Research/Breeze-7B-Instruct-v0_1
- Azure99/blossom-v4-mistral-7b
---
# Breezeblossom-v4-mistral-2x7B
Breezeblossom-v4-mistral-2x7B is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [MediaTek-Research/Breeze-7B-Instruct-v0_1](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v0_1)
* [Azure99/blossom-v4-mistral-7b](https://huggingface.co/Azure99/blossom-v4-mistral-7b)
## 🧩 Configuration
```yamlbase_model: MediaTek-Research/Breeze-7B-Instruct-v0_1
gate_mode: hidden
dtype: float16
experts:
- source_model: MediaTek-Research/Breeze-7B-Instruct-v0_1
positive_prompts: [ "<s>You are a helpful AI assistant built by MediaTek Research. The user you are helping speaks Traditional Chinese and comes from Taiwan. [INST] 你好,請問你可以完成什麼任務? [/INST] "]
- source_model: Azure99/blossom-v4-mistral-7b
positive_prompts: ["A chat between a human and an artificial intelligence bot. The bot gives helpful, detailed, and polite answers to the human's questions. \n|Human|: hello\n|Bot|: "]```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "sam-ezai/Breezeblossom-v4-mistral-2x7B"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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"])
``` |