Instructions to use TIGER-Lab/MAmmoTH2-8B-Plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TIGER-Lab/MAmmoTH2-8B-Plus with Transformers:

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

pipe = pipeline("text-generation", model="TIGER-Lab/MAmmoTH2-8B-Plus")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TIGER-Lab/MAmmoTH2-8B-Plus")
model = AutoModelForCausalLM.from_pretrained("TIGER-Lab/MAmmoTH2-8B-Plus", 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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TIGER-Lab/MAmmoTH2-8B-Plus with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TIGER-Lab/MAmmoTH2-8B-Plus"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TIGER-Lab/MAmmoTH2-8B-Plus",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TIGER-Lab/MAmmoTH2-8B-Plus

SGLang

How to use TIGER-Lab/MAmmoTH2-8B-Plus 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 "TIGER-Lab/MAmmoTH2-8B-Plus" \
    --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": "TIGER-Lab/MAmmoTH2-8B-Plus",
		"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 "TIGER-Lab/MAmmoTH2-8B-Plus" \
        --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": "TIGER-Lab/MAmmoTH2-8B-Plus",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TIGER-Lab/MAmmoTH2-8B-Plus with Docker Model Runner:
```
docker model run hf.co/TIGER-Lab/MAmmoTH2-8B-Plus
```

gguf version?

by KnutJaegersberg - opened May 7, 2024

Discussion

KnutJaegersberg

May 7, 2024

I've tried to convert this model into a gguf model, but there was an issue with the tokenizer. Will you try to make converts, too? would greatly expand the user base!

KnutJaegersberg

May 8, 2024

it looks like you forgot to add the tokenizer.json file here

aaabiao

May 8, 2024

I apologize for the oversight. Thank you for bringing it to my attention. The tokenizer.json file has been uploaded now. If you need any further assistance, please don't hesitate to let me know. Thank you for your understanding.

KnutJaegersberg changed discussion status to closed May 8, 2024

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