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---
license: apache-2.0
tags:
- moe
- merge
- mergekit
- 01-ai/Yi-6B-Chat
- HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca
base_model:
- 01-ai/Yi-6B-Chat
- HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca
---
# Boundary-Coder-Yi-2x6B-MoE
Boundary-Coder-Yi-2x6B-MoE is a Mixture of Experts (MoE) made with the following models:
* [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat)
* [HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca](https://huggingface.co/HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca)
## 🧩 Configuration
```yaml
base_model: 01-ai/Yi-6B-Chat
gate_mode: hidden
experts:
- source_model: 01-ai/Yi-6B-Chat
positive_prompts:
- "chat"
- "assistant"
- "tell me"
- "explain"
- "I want"
- source_model: HenryJJ/Instruct_Yi-6B_Dolly_CodeAlpaca
positive_prompts:
- "code"
- "python"
- "javascript"
- "programming"
- "algorithm"
dtype: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "NotAiLOL/Boundary-Coder-Yi-2x6B-MoE"
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"])
``` |