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const main = async () => {
const result = await fetch('https://api.ai.cc/v1/chat/completions', {
method: 'POST',
headers: {
Authorization: 'Bearer ',
'Content-Type': 'application/json',
},
body: JSON.stringify({
model: 'llava-hf/llava-v1.6-mistral-7b-hf',
max_tokens: 1024,
messages: [
{
role: 'user',
content: [
{
type: 'text',
text: 'What’s in this image?',
},
{
role: 'user',
type: 'image_url',
image_url: {
url: 'https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg',
},
},
],
},
],
}),
}).then((res) => res.json());
const message = result.choices[0].message.content;
console.log(\`Assistant: \${message}\`);
};
main();
import os
from together import Together
client = Together(base_url="https://api.ai.cc/v1", api_key="")
def main():
response = client.chat.completions.create(
model="llava-hf/llava-v1.6-mistral-7b-hf",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "What sort of animal is in this picture? What is its usual diet? What area is the animal native to? And isn’t there some AI model that’s related to the image?",
},
{
"type": "image_url",
"image_url": {
"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/3/3a/LLama.jpg/444px-LLama.jpg?20050123205659",
},
},
],
}
],
max_tokens=1024,
)
print("Assistant: ", response.choices[0].message.content)
if __name__ == '__main__':
main()
-
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Product Detail
✨ LLaVA v1.6 - Mistral 7B: A Multimodal AI Breakthrough
Discover LLaVA v1.6 - Mistral 7B, an advanced open-source multimodal language model that seamlessly integrates text and image understanding. Developed by Haotian Liu and released in December 2023, this Version 1.6 model is built to redefine human-AI interaction across diverse applications.
- Model Name: LLaVA v1.6 - Mistral 7B
- Developer: Haotian Liu
- Release Date: December 2023
- Version: 1.6
- Model Type: Multimodal Language Model (Text and Image)
💡 Key Features & Capabilities
LLaVA v1.6 - Mistral 7B stands out with its robust design and user-centric enhancements:
- ✅ Foundation Model: Powered by the highly capable Mistral-7B-Instruct-v0.2 base model.
- ✅ Dynamic Image Input: Supports high-resolution image inputs, adapting dynamically for superior visual context.
- ✅ Multimodal Task Mastery: Expertly handles a wide array of tasks combining text and vision.
- ✅ Enhanced Licensing & Bilingual Support: Offers improved commercial licensing terms and stronger bilingual capabilities.
- ✅ Efficient Design: Boasts 7 billion parameters, balancing performance with efficient computation.
🚀 Intended Applications
This versatile model is engineered for a variety of innovative applications:
- 📚 Research and development in large multimodal models and chatbots.
- 🖼️ Advanced image captioning and visual question answering (VQA).
- 💬 Engaging open-ended dialogues enriched with visual context.
- 🤖 Building intelligent virtual assistants and conversational AI.
- 🔍 Image-based search and retrieval systems.
- 🎓 Interactive educational tools utilizing visual learning.
The model offers strong multilingual capabilities, notably improved bilingual support compared to its predecessors.
⚙️ Technical Specifications
Architecture Overview
LLaVA v1.6 - Mistral 7B is built upon a sophisticated architecture:
- 🧠 An auto-regressive language model, leveraging the robust transformer architecture.
- 👁️ A powerful pre-trained vision encoder (likely CLIP-L, consistent with similar models).
- 🔗 Seamless integration of text and image inputs using the
<image>token within prompts.
Training Data Insights
The model's extensive capabilities stem from training on a diverse and comprehensive dataset, totaling over 1.3 million unique samples:
- 📊 558K filtered image-text pairs from LAION/CC/SBU, expertly captioned by BLIP.
- 🗣️ 158K GPT-generated multimodal instruction-following data.
- 📚 500K academic-task-oriented VQA data mixture.
- 🧠 50K GPT-4V data mixture.
- 💬 40K ShareGPT data.
Knowledge Cutoff: December 2023.
Diversity and Bias: The wide range of training data sources significantly contributes to reducing potential biases, enhancing the model's fairness and applicability.
Performance Benchmarks
LLaVA v1.6 - Mistral 7B consistently demonstrates strong performance across critical benchmarks:
Comparative Analysis
The model exhibits highly competitive performance when compared to other leading models:
- 📈 Accuracy: Achieves impressive scores, including 35.3 on MMMU and 37.7 on MathVista benchmarks.
- ⚡ Speed: While specific inference speed metrics are not detailed, its 7 billion parameter size suggests efficient and responsive computation.
- 🛡️ Robustness: Consistently strong performance across diverse benchmarks and tasks underscores its excellent generalization capabilities.
📚 Usage & Ethical Considerations
Code Samples
Developers can integrate LLaVA v1.6 - Mistral 7B using standard API calls. Here’s a conceptual example for chat completion with vision:
// Example API call for LLaVA v1.6 - Mistral 7B
fetch('https://api.together.xyz/v1/chat/completions', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY',
},
body: JSON.stringify({
model: 'llava-hf/llava-v1.6-mistral-7b-hf',
messages: [
{role: 'system', content: 'You are a helpful assistant.'},
{role: 'user', content: [
{type: 'text', text: 'What is in this image?'},
{type: 'image_url', image_url: {url: 'data:image/jpeg;base64,...'}}
]}
]
})
})
.then(response => response.json())
.then(data => console.log(data));
Ethical Guidelines
While specific detailed guidelines are not explicitly provided within the model's description, users are strongly encouraged to adhere to responsible AI practices. It is crucial to consider potential biases in model outputs and ensure the model is never used for generating harmful, misleading, or illicit content.
Licensing Information
LLaVA v1.6 - Mistral 7B operates under the licensing terms of its base model, the Mistral-7B-Instruct-v0.2. Users must consult the official licensing documentation for specific usage rights, restrictions, and compliance requirements.
❓ Frequently Asked Questions (FAQs)
Q1: What is LLaVA v1.6 - Mistral 7B?
A1: LLaVA v1.6 - Mistral 7B is an open-source, multimodal language model capable of understanding and generating text based on both textual and visual inputs. It combines a large language model with a pre-trained vision encoder.
Q2: What are the primary applications of this model?
A2: It is ideal for research on multimodal AI, image captioning, visual question answering, open-ended dialogue with visual context, building virtual assistants, and image-based search applications.
Q3: Does LLaVA v1.6 - Mistral 7B support multiple languages?
A3: Yes, the model demonstrates strong multilingual capabilities, with significant improvements in bilingual support compared to earlier versions.
Q4: What is the knowledge cutoff date for the model's training data?
A4: The knowledge cutoff for LLaVA v1.6 - Mistral 7B's training data is December 2023.
Q5: How does its performance compare to other models?
A5: LLaVA v1.6 - Mistral 7B shows competitive performance, achieving scores like 35.3 on MMMU and 37.7 on MathVista benchmarks, indicating strong accuracy and generalization capabilities.
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