Instructions to use mixtao/MixTAO-7Bx2-MoE-v8.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mixtao/MixTAO-7Bx2-MoE-v8.1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="mixtao/MixTAO-7Bx2-MoE-v8.1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("mixtao/MixTAO-7Bx2-MoE-v8.1")
model = AutoModelForCausalLM.from_pretrained("mixtao/MixTAO-7Bx2-MoE-v8.1", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mixtao/MixTAO-7Bx2-MoE-v8.1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mixtao/MixTAO-7Bx2-MoE-v8.1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mixtao/MixTAO-7Bx2-MoE-v8.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mixtao/MixTAO-7Bx2-MoE-v8.1

SGLang

How to use mixtao/MixTAO-7Bx2-MoE-v8.1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "mixtao/MixTAO-7Bx2-MoE-v8.1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mixtao/MixTAO-7Bx2-MoE-v8.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "mixtao/MixTAO-7Bx2-MoE-v8.1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mixtao/MixTAO-7Bx2-MoE-v8.1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mixtao/MixTAO-7Bx2-MoE-v8.1 with Docker Model Runner:
```
docker model run hf.co/mixtao/MixTAO-7Bx2-MoE-v8.1
```

zhengr commited on May 16, 2024

Commit

d6c689e

verified ·

1 Parent(s): 16bf59f

Update README.md

Browse files

Files changed (1) hide show

README.md +1 -1

README.md CHANGED Viewed

@@ -123,7 +123,7 @@ This model is mainly used for large model technology experiments, and increasing
 | --- | --- |
 |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1y2XmAGrQvVfbgtimTsCBO3tem735q7HZ?usp=sharing) | MixTAO-7Bx2-MoE-v8.1 |
 |[mixtao-7bx2-moe-v8.1.Q4_K_M.gguf](https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-v8.1-GGUF/resolve/main/mixtao-7bx2-moe-v8.1.Q4_K_M.gguf) | GGUF of MixTAO-7Bx2-MoE-v8.1 <br> Only Q4_K_M in https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-v8.1-GGUF |
-| Demo Space | https://zhengr-mixtao-7bx2-moe-v8-1.hf.space/ |
 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_zhengr__MixTAO-7Bx2-MoE-v8.1)

 | --- | --- |
 |[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1y2XmAGrQvVfbgtimTsCBO3tem735q7HZ?usp=sharing) | MixTAO-7Bx2-MoE-v8.1 |
 |[mixtao-7bx2-moe-v8.1.Q4_K_M.gguf](https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-v8.1-GGUF/resolve/main/mixtao-7bx2-moe-v8.1.Q4_K_M.gguf) | GGUF of MixTAO-7Bx2-MoE-v8.1 <br> Only Q4_K_M in https://huggingface.co/zhengr/MixTAO-7Bx2-MoE-v8.1-GGUF |
+| Demo Space | https://huggingface.co/spaces/zhengr/MixTAO-7Bx2-MoE-v8.1/ |
 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_zhengr__MixTAO-7Bx2-MoE-v8.1)