Welcome to the exciting world of Typhoon-0130, the innovative Thai large language model that comprises 7 billion parameters. This instruct model is designed to understand and follow instructions efficiently, leveraging similar techniques and datasets as notable models such as ORCA and OpenChat. Let’s dive into how you can deploy and utilize this incredible tool in your projects!

Getting Started with Typhoon-0130

Before you launch into using this powerful model, here’s what you need to know:

• Model Type: 7B instruct decoder-only model based on Mistral architecture
• Requirements: You will need transformers version 4.38.0 or newer
• Primary Languages: Thai 🇹🇭 and English 🇬🇧
• License: Apache-2.0

Deploying the Model

For production deployment, it’s recommended to utilize the OpenAI-compatible API server provided by the vLLM project. Follow these steps:

• Open your terminal and run the following command:

python -m vllm.entrypoints.openai.api_server --port 8080 --model scb10xtyphoon-7b-instruct-01-30-2024 --max-num-batched-tokens 8192 --max-model-len 8192 --served-model-name typhoon-instruct

This command sets up the necessary API server for utilizing the Typhoon-0130 model efficiently!

Using the Chat Template

To interact with the model, you can use the chatml chat-template. Here’s how you format your messages:

for message in messages:
    im_start + message[role] + n + message[content]
    if (loop.last and add_generation_prompt) or not loop.last:
        im_end + n
    endif
endfor
if add_generation_prompt and messages[-1][role] != assistant:
    im_start + assistant + n
endif

Think of this template as a detailed recipe where each ingredient (message) contributes to the final dish (the conversation with the model). By structuring your prompts correctly, you ensure the model understands precisely what you need, much like following a cooking recipe to create a delicious meal!

Intended Uses & Limitations

Remember, Typhoon-0130 is still under development. It’s crucial to understand its intended uses and limitations:

• This model is primarily designed for instructional applications.
• It has some guardrails to prevent inappropriate responses, but it may still produce inaccurate or biased answers.

As a developer, it’s vital to assess these risks based on your application context.

Troubleshooting Tips

If you encounter any issues during setup or usage, here are some common troubleshooting ideas:

• Model Not Responding: Ensure your API server is correctly running on the specified port (8080) and that you have the right version of the transformers library installed.
• Unexpected Errors: Double-check your command syntax and verify the parameters set in the script. Sometimes, simple typos can lead to confusion.
• Inaccurate Responses: Be specific in your prompts. Just like asking a friend for directions, the more details you provide, the clearer the answer you’ll get!

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.

Stay Connected

For additional resources, updates, or support, feel free to follow the Typhoon team on Twitter or join their Discord channel.