SiliconCloud, Production Ready
Cloud with Low Cost
Teaming up with excellent open-source foundation models.
SiliconCloud, Production Ready
Cloud with Low Cost
Teaming up with excellent open-source foundation models.
Top-quality model services
01.
Chat
SiliconCloud delivers efficient, user-friendly, and scalable LLM models, with an out-of-the-box inference acceleration capability, including Llama3, Mixtral, Qwen, Deepseek, etc.
02.
Image
SiliconCloud encompasses a diverse range of text-to-image and text-to-video models, such as SDXL, SDXL lightning, photomaker, instantid, and so on.
01.
Chat
SiliconCloud delivers efficient, user-friendly, and scalable LLM models, with an out-of-the-box inference acceleration capability, including Llama3, Mixtral, Qwen, Deepseek, etc.
02.
Image
SiliconCloud encompasses a diverse range of text-to-image and text-to-video models, such as SDXL, SDXL lightning, photomaker, instantid, and so on.
Serverless GenAI services
Serverless GenAI services
01.
Chat
SiliconCloud delivers efficient, user-friendly, and scalable LLM models, with an out-of-the-box inference acceleration capability, including Llama3, Mixtral, Qwen, Deepseek, etc.
02.
Image
03.
more
01.
Chat
SiliconCloud delivers efficient, user-friendly, and scalable LLM models, with an out-of-the-box inference acceleration capability, including Llama3, Mixtral, Qwen, Deepseek, etc.
02.
Image
03.
more
One-Stop: From Fine-Tune to Deploying
One-Stop: From Fine-Tune to Deploying
designed for large-scale model fine-tuning and deploying. Through the platform, users can quickly and seamlessly deploy custom models as services and fine-tune them based on the data uploaded.
designed for large-scale model fine-tuning and deploying. Through the platform, users can quickly and seamlessly deploy custom models as services and fine-tune them based on the data uploaded.
designed for large-scale model fine-tuning and deploying. Through the platform, users can quickly and seamlessly deploy custom models as services and fine-tune them based on the data uploaded.
Blazing fsat model inference
Blazing fsat model inference
Blazing fsat model inference
Time latency of LLM is reduced by up to 2.7 times
Time latency of LLM is reduced by up to 2.7 times
Time latency of LLM is reduced by up to 2.7 times
Speed of text to image is increased by 3 times
Speed of text to image is increased by 3 times
Speed of text to image is increased by 3 times
Auto-scaling on demand
Auto-scaling on demand
Auto-scaling on demand
1.
1.
Create an auto-scaling group which contains a collection of SiliconCloud instances.
Create an auto-scaling group which contains a collection of SiliconCloud instances.
2.
2.
Specify minimum and maximum numbers of instance in that group.
Specify minimum and maximum numbers of instance in that group.
1.
Create an auto-scaling group which contains a collection of SiliconCloud instances.
2.
Specify minimum and maximum numbers of instance in that group.
3.
Specify desired capacity and auto-scaling policies.
3.
3.
4.
Specify desired capacity and auto-scaling policies.
Specify desired capacity and auto-scaling policies.
Created successfully. The platform will automatically scales the service on demand.
4.
4.
Created successfully. The platform will automatically scales the service on demand.
Created successfully. The platform will automatically scales the service on demand.
Fine-tuning to deployment one-stop service
Fine-tuning to deployment one-stop service
Fine-tuning to deployment one-stop service
Data Upload
Data Upload
Data Upload
Build a suitable dataset and upload it for creating fine-tuning jobs. The data set consists of a single JSONL file, where each line is a separate training example.
Build a suitable dataset and upload it for creating fine-tuning jobs. The data set consists of a single JSONL file, where each line is a separate training example.
Build a suitable dataset and upload it for creating fine-tuning jobs. The data set consists of a single JSONL file, where each line is a separate training example.
Step.01→
Step.01→
Step.01→
Fine-tuning
Fine-tuning
Fine-tuning
Select the appropriate dataset and adjust the relevant parameters to improve the model effect and meet the customization needs.
Select the appropriate dataset and adjust the relevant parameters to improve the model effect and meet the customization needs.
Select the appropriate dataset and adjust the relevant parameters to improve the model effect and meet the customization needs.
Step.02→
Step.02→
Step.02→
Effect Evaluation
Effect Evaluation
Effect Evaluation
Upload the evaluation dataset. Evaluate the effect of the trained model, and choose tge best one for deployment.
Upload the evaluation dataset. Evaluate the effect of the trained model, and choose tge best one for deployment.
Upload the evaluation dataset. Evaluate the effect of the trained model, and choose tge best one for deployment.
Step.03→
Step.03→
Step.03→
Model Deploying
Model Deploying
Model Deploying
Deploy the fine-tuned model on the cloud platform and call it through APIs.
Deploy the fine-tuned model on the cloud platform and call it through APIs.
Deploy the fine-tuned model on the cloud platform and call it through APIs.
Step.04
Step.04
Step.04
Easy to use
Easy to use
Easy to use
from openai import OpenAI
client = OpenAI(api_key="YOUR_API_KEY", base_url="https://api.siliconflow.cn/v1")
response = client.chat.completions.create(
model='alibaba/Qwen1.5-110B-Chat',
messages=[
{'role': 'user', 'content': "抛砖引玉是什么意思呀"}
],
stream=True
)
for chunk in response:
print(chunk.choices[0].delta.content)
from openai import OpenAI
client = OpenAI(api_key="YOUR_API_KEY", base_url="https://api.siliconflow.cn/v1")
response = client.chat.completions.create(
model='alibaba/Qwen1.5-110B-Chat',
messages=[
{'role': 'user', 'content': "抛砖引玉是什么意思呀"}
],
stream=True
)
for chunk in response:
print(chunk.choices[0].delta.content)
from openai import OpenAI
client = OpenAI(api_key="YOUR_API_KEY", base_url="https://api.siliconflow.cn/v1")
response = client.chat.completions.create(
model='alibaba/Qwen1.5-110B-Chat',
messages=[
{'role': 'user', 'content': "抛砖引玉是什么意思呀"}
],
stream=True
)
for chunk in response:
print(chunk.choices[0].delta.content)
Model Inference
Model Inference
Model Inference
With just a single line of code, developers can seamlessly integrate the fastest model services from SiliconCloud.
With just a single line of code, developers can seamlessly integrate the fastest model services from SiliconCloud.
With just a single line of code, developers can seamlessly integrate the fastest model services from SiliconCloud.
Model Deploy
Model Deploy
Model Deploy
·
·
Upload your workflow and Download the callable Model Service API.
Upload your workflow and Download the callable Model Service API.
Upload your workflow and Download the callable Model Service API.
·
·
Reduce the chances of application downtime with auto scaling.
Reduce the chances of application downtime with auto scaling.
Reduce the chances of application downtime with auto scaling.
·
·
Accelerate your workflow as needed.
Accelerate your workflow as needed.
Accelerate your workflow as needed.
Multiple service modes
meet enterprise-level standardized delivery
Serverless Deployment
Built for developers
High-performance inference, industry-leading speed
Diverse models, covering multiple scenarios
Pay-as-you-go, per-token pricing
Serverless rate limits
On-demand Deployment
Enhanced for enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Reserved Capacity
Enhanced for enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Competitive Unit Pricing
Prioritize using the latest product features
Multiple service mode
meet enterprise-level standardized delivery
Serverless Deployment
Built for developers
High-performance inference, industry-leading speed
Diverse models, covering multiple scenarios
Pay-as-you-go, per-token pricing
Serverless rate limits
On-demand Deployment
Enhanced for enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Reserved Capacity
Enhanced for enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Competitive Unit Pricing
Prioritize using the latest product features
Multiple service mode
meet enterprise-level standardized delivery
Serverless Deployment
Built for developers
High-performance inference, industry-leading speed
Diverse models, covering multiple scenarios
Pay-as-you-go, per-token pricing
Serverless rate limits
On-demand Deployment
Enhanced for enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Reserved Capacity
Enhanced for enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Competitive Unit Pricing
Prioritize using the latest product features
Multiple service mode
meet enterprise-level standardized delivery
Serverless Deployment
Built for developers
High-performance inference, industry-leading speed
Diverse models, covering multiple scenarios
Pay-as-you-go, per-token pricing
Serverless rate limits
On-demand Deployment
Built For enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Reserved Capacity
Enhanced for enterprises
Custom models tailored to your needs
Configurable strategies optimization
Isolated resources for high QoS
Custom enterprise rate limiting
Competitive Unit Pricing
Prioritize using the latest product features
Accelerate AGI to Benefit Humanity
Accelerate AGI to Benefit Humanity
OneDiff, High-performance
Image Generation Engine
Teaming up with excellent open-source foundation models.