Instructions to use tencent/Hy3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tencent/Hy3 with Transformers:

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

pipe = pipeline("text-generation", model="tencent/Hy3")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tencent/Hy3")
model = AutoModelForCausalLM.from_pretrained("tencent/Hy3")
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 tencent/Hy3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tencent/Hy3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tencent/Hy3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tencent/Hy3

SGLang

How to use tencent/Hy3 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 "tencent/Hy3" \
    --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": "tencent/Hy3",
		"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 "tencent/Hy3" \
        --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": "tencent/Hy3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tencent/Hy3 with Docker Model Runner:
```
docker model run hf.co/tencent/Hy3
```

Vision?

by seamon67 - opened 6 days ago

Discussion

seamon67

6 days ago

Any plans to add Multimodal vision support?

yiqichen01

Tencent org 6 days ago

Thanks for your interest! We understand that multimodal vision support is an important and highly requested direction.

At this moment, we don’t have a concrete timeline or details to share, but we’ll continue to evaluate future capabilities based on user feedback and project priorities. Please stay tuned for updates.

seamon67

6 days ago

Thanks for your interest! We understand that multimodal vision support is an important and highly requested direction.

At this moment, we don’t have a concrete timeline or details to share, but we’ll continue to evaluate future capabilities based on user feedback and project priorities. Please stay tuned for updates.

You guys just have to believe in yourself and your ability to release multimodal vision.

pfn0

3 days ago

multimodal is one of my hard requirements in selecting a model to run.

seamon67

3 days ago

Like we can show a screenshot of GTA 6 and say "Go make GTA 7"

seamon67

3 days ago

In all seriousness, it's way easier to describe a complex problem to a model when there's vision.
Text input is pretty much never enough. Visual Context helps a lot.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

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