



const { OpenAI } = require('openai');
const api = new OpenAI({
baseURL: 'https://api.ai.cc/v1',
apiKey: '',
});
const main = async () => {
const result = await api.chat.completions.create({
model: 'databricks/dbrx-instruct',
messages: [
{
role: 'system',
content: 'You are an AI assistant who knows everything.',
},
{
role: 'user',
content: 'Tell me, why is the sky blue?'
}
],
});
const message = result.choices[0].message.content;
console.log(`Assistant: ${message}`);
};
main();
import os
from openai import OpenAI
client = OpenAI(
base_url="https://api.ai.cc/v1",
api_key="",
)
response = client.chat.completions.create(
model="databricks/dbrx-instruct",
messages=[
{
"role": "system",
"content": "You are an AI assistant who knows everything.",
},
{
"role": "user",
"content": "Tell me, why is the sky blue?"
},
],
)
message = response.choices[0].message.content
print(f"Assistant: {message}")

Product Detail
💻 Introducing DBRX Instruct: A New Era of Open LLMs
DBRX Instruct, developed by Databricks, is a groundbreaking large language model (LLM) designed to set new benchmarks in performance and efficiency. Released in 2023, this version 1.0 Instruct model leverages a sophisticated architecture to deliver superior capabilities across a wide spectrum of natural language processing tasks.
- ● Model Name: DBRX
- ● Developer/Creator: Databricks
- ● Release Date: 2023
- ● Version: 1.0 Instruct
- ● Model Type: Large Language Model (LLM)
🔥 Key Architectural & Performance Highlights
At its core, DBRX Instruct utilizes a fine-grained Mixture-of-Experts (MoE) architecture. This innovative design incorporates 132 billion total parameters, with a dynamic activation of 36 billion parameters for any given input, ensuring optimal efficiency and performance.
✨ Core Features:
- ✓ Advanced MoE System: Features 16 experts capable of selecting 4, offering 65x more possible expert combinations than other prominent open MoE models.
- ✓ Extensive Training Data: Pre-trained on an impressive 12 trillion tokens of meticulously curated text and code data.
- ✓ Benchmark Dominance: Demonstrates exceptional performance across critical benchmarks including general knowledge, commonsense reasoning, programming, and mathematical reasoning.
- ✓ Outperforms Peers: Consistently surpasses leading open models such as Mixtral Instruct and Code Llama (70B) in various evaluations.
📜 Intended Use Cases & Multilingual Support
DBRX Instruct is engineered as a general-purpose LLM, making it incredibly versatile for a multitude of natural language processing (NLP) applications.
💬 Ideal For:
- ✍ Text Generation: Crafting coherent and contextually relevant text.
- ❓ Question Answering: Providing accurate and insightful responses to queries.
- 💻 Code Generation: Generating high-quality code snippets and solving programming challenges.
- 🔢 Mathematical Reasoning: Excelling in tasks requiring complex mathematical understanding.
Furthermore, DBRX Instruct stands out as a multilingual model, capable of processing and generating content across a broad spectrum of languages, enhancing its global applicability.
🔗 Deep Dive: Technical Specifications & Performance
Architecture
DBRX Instruct is built upon a transformer-based, decoder-only LLM architecture, trained using the next-token prediction objective. Its fine-grained MoE setup involves 16 distinct experts, dynamically selecting 4 for each input query to optimize processing.
Training Data Quality
The model's robust capabilities stem from its pre-training on 12 trillion tokens of meticulously curated text and code data. With a maximum context length of 32,000 tokens, this dataset is estimated to be at least twice the quality of data used for the MPT family of models, ensuring a rich understanding and generation capacity.
📈 Performance Metrics vs. Leading Models:
DBRX Instruct consistently demonstrates superior performance against other leading open models on standard benchmarks:
- MMLU: 73.7% (DBRX Instruct) vs. 71.4% (Mixtral Instruct)
- HellaSwag 10-shot: 89.0% (DBRX Instruct) vs. 87.6% (Mixtral Instruct)
- WinoGrande: 81.8% (DBRX Instruct) vs. 81.1% (Mixtral Instruct)
- Databricks Gauntlet: 66.8% (DBRX Instruct) vs. 60.7% (Mixtral Instruct)
- HumanEval: 70.1% (DBRX Instruct) vs. 54.8% (Mixtral Instruct)
- GSM8k: 66.9% (DBRX Instruct) vs. 61.1% (Mixtral Instruct)
💡 Getting Started with DBRX Instruct
API Access
DBRX Instruct is designed for easy integration via API. An example API snippet (e.g., `open-ai.chat-completion` with `databricks/dbrx-instruct`) demonstrates its straightforward usability for developers.
📝 Licensing Information
DBRX Instruct is available for use under the Databricks Open Model License, promoting broad access and innovation.
💬 Frequently Asked Questions (FAQ)
-
Q: What is the DBRX Instruct model?
A: DBRX Instruct is a powerful, open-source large language model (LLM) developed by Databricks, known for its fine-grained Mixture-of-Experts (MoE) architecture and strong performance across various NLP tasks.
-
Q: How does DBRX Instruct differ from other LLMs?
A: It uses a unique MoE architecture with 16 experts (selecting 4 per input), offering significantly more expert combinations and outperforming leading open models like Mixtral Instruct and Code Llama (70B) on key benchmarks.
-
Q: What are the primary applications of DBRX Instruct?
A: It's a general-purpose LLM ideal for text generation, question answering, code generation, and tasks requiring strong programming and mathematical reasoning capabilities.
-
Q: Is DBRX Instruct multilingual?
A: Yes, DBRX Instruct supports a wide range of languages, making it suitable for global applications.
-
Q: Under what license is DBRX Instruct available?
A: DBRX Instruct is released under the Databricks Open Model License.
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