Model Invocation¶
Hydra offers two ways to host large models. You can choose either based on your needs:
- MaaS by Token: Token-based usage with shared resources. Users can invoke models without deploying their own instances.
- Model Service: Dedicated model instances for users, with unlimited API calls.
Currently Supported Models and Hosting Methods¶
Model Name | MaaS by Token | Model Service |
---|---|---|
🔥 DeepSeek-R1 | ✅ | |
🔥 DeepSeek-V3 | ✅ | |
Phi-4 | ✅ | |
Phi-3.5-mini-instruct | ✅ | |
Qwen2-0.5B-Instruct | ✅ | |
Qwen2.5-7B-Instruct | ✅ | ✅ |
Qwen2.5-14B-Instruct | ✅ | |
Qwen2.5-Coder-32B-Instruct | ✅ | |
Qwen2.5-72B-Instruct-AWQ | ✅ | ✅ |
baichuan2-13b-Chat | ✅ | |
Llama-3.2-11B-Vision-Instruct | ✅ | ✅ |
glm-4-9b-chat | ✅ | ✅ |
Model Endpoint¶
A model endpoint is a URL or API address through which users can send requests to perform inference with the model.
Invocation Type | Endpoint |
---|---|
MaaS by Token | chat.d.run |
Model Service | <region>.d.run |
API Invocation Examples¶
Using MaaS by Token¶
To invoke a model using MaaS by Token:
- Get an API Key: Log in to the user console and create a new API Key.
- Set the Endpoint: Set your SDK endpoint to
chat.d.run
. - Call the Model: Use the official model name and your API Key.
Sample Code (Python):
import openai
openai.api_key = "your-api-key" # Replace with your actual API Key
openai.api_base = "https://chat.d.run"
response = openai.Completion.create(
model="public/deepseek-r1",
prompt="What is your name?"
)
print(response.choices[0].text)
Using Dedicated Model Service¶
To invoke a self-deployed model instance:
- Deploy a Model Instance: Deploy a model in a designated region, such as
sh-02
. - Get an API Key: Log in to the user console and create a new API Key.
- Set the Endpoint: Replace the SDK endpoint with
<region>.d.run
, e.g.,sh-02.d.run
. - Call the Model: Use the official model name and your API Key.
Sample Code (Python):
import openai
openai.api_key = "your-api-key" # Replace with your actual API Key
openai.api_base = "https://sh-02.d.run" # Replace with your model region
response = openai.Completion.create(
model="u-1100a15812cc/qwen2", # Replace with your deployed model name
prompt="What is your name?"
)
print(response.choices[0].text)
Frequently Asked Questions¶
Q1: How do I choose an invocation method?¶
- MaaS by Token: Best for lightweight or infrequent use cases.
- Instance (Model Service): Ideal for high-performance, frequent usage scenarios.
Q2: How do I view my API Key?¶
Log in to the user console and go to the API Key management page. See API Key Management for details.
Q3: How do I get the model name?¶
- For MaaS by Token, the model name uses the format
public/<model-name>
, e.g.,public/deepseek-r1
, and can be found on the model details page. - For Model Service, the model name includes your username, e.g.,
u-1100a15812cc/qwen2
, and can be copied directly from the model list.