README.md

metadata

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:

• MediaTek-Research/Breeze-7B-Instruct-v0_1
• Azure99/blossom-v4-mistral-7b

🧩 Configuration

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"])