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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: 'Phind/Phind-CodeLlama-34B-v2',
messages: [
{
role: 'system',
content: 'You are SQL code assistant.',
},
{
role: 'user',
content: 'Could you please provide me with an example of a database structure that I could use for a project in MySQL?'
}
],
});
const message = result.choices[0].message.content;
console.log(\`Assistant: \${message}\`);
};
main();
import os
from openai import OpenAI
def main():
client = OpenAI(
api_key="",
base_url="https://api.ai.cc/v1",
)
response = client.chat.completions.create(
model="Phind/Phind-CodeLlama-34B-v2",
messages=[
{
"role": "system",
"content": "You are SQL code assistant.",
},
{
"role": "user",
"content": "Could you please provide me with an example of a database structure that I could use for a project in MySQL?",
},
],
)
message = response.choices[0].message.content
print(f"Assistant: {message}")
if __name__ == "__main__":
main()
-
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Product Detail
Welcome to the forefront of software development with Phind Code LLaMA v2 (34B), an advanced AI model engineered to revolutionize how developers write, understand, and debug code. Built upon the robust LLaMA architecture and boasting an impressive 34 billion parameters, this model provides unparalleled precision and context-aware suggestions across a multitude of programming languages.
💻 Unleash Advanced Code Intelligence
Phind Code LLaMA v2 (34B) stands as a cutting-edge large language model meticulously fine-tuned for programming tasks. It's designed to be an indispensable tool for developers aiming to optimize their coding workflow, offering capabilities from intelligent bug fixes to generating entire codebases from scratch. Its integration via the Phind Code API grants users direct access to this powerful AI assistant, transforming complex coding challenges into manageable tasks.
📊 Model Specifications
Model Name: Phind-CodeLlama-34B-Python-v1
Developer/Creator: Phind
Release Date: May 2023
Version: 1.0
Model Type: Large language model fine-tuned for programming
🗃 Version History
- Phind/Phind-CodeLlama-34B-Python-v1: The initial release, optimized specifically for Python code generation. Achieved 69.5% on HumanEval benchmark.
- Phind/Phind-CodeLlama-34B-v2: The latest and enhanced iteration of the model, demonstrating superior performance with 73.8% on HumanEval.
📣 Specialized vs. General-Purpose AI
Unlike general-purpose models such as GPT or Codex, Phind Code LLaMA v2 (34B) differentiates itself with a specialized focus on intricate coding tasks. Its architecture is meticulously trained on diverse codebases, enabling it to comprehend and generate code with exceptional accuracy and relevance. This targeted specialization makes it the preferred choice for demanding software development applications, providing more precise and efficient coding assistance.
💡 Tips for Maximizing Efficiency
To harness the full potential of the Phind Code LLaMA v2 (34B) API, consider adopting these best practices:
- ✍️ Detailed Prompts: Provide clear, concise, and specific instructions to significantly enhance the relevance and quality of the generated code.
- 🔄 Iterative Refinement: Utilize the model's initial output as a foundation, then refine your requests iteratively to converge on the ideal solution.
- 📚 Leverage Examples: Incorporating relevant code examples into your prompts can effectively guide the AI to produce code that aligns precisely with your requirements.
- ⚠️ Understand Limitations: While immensely powerful, it is crucial to diligently review and thoroughly test any generated code, particularly for critical or production-level applications.
🚀 Optimizing Your Workflow with Phind Code LLaMA v2 (34B)
Integrating Phind Code LLaMA v2 (34B) into your development lifecycle promises to dramatically accelerate coding tasks, from the initial ideation phase all the way to deployment. Its sophisticated ability to understand context and generate highly relevant code snippets fundamentally transforms the developer's approach to coding challenges, fostering a more efficient, productive, and creative workflow. Whether you are a seasoned software engineer or just embarking on your coding journey, Phind Code LLaMA v2 (34B) equips you with the advanced tools necessary to elevate your coding capabilities to unprecedented levels.
💻 API Example
# Example using Phind Code API (Conceptual)
import phind_api
client = phind_api.PhindClient(api_key="YOUR_PHIND_API_KEY")
response = client.generate_code(
model="Phind/Phind-CodeLlama-34B-v2",
prompt="Write a Python function to calculate the factorial of a number.",
temperature=0.7,
max_tokens=150
)
print(response.choices[0].text)
# Expected output (simplified):
# def factorial(n):
# if n == 0:
# return 1
# else:
# return n * factorial(n-1)
Note: The above is a conceptual API usage example. Please refer to the official Phind Code API documentation for exact implementation details.
❓ Frequently Asked Questions (FAQ)
Q: What is Phind Code LLaMA v2 (34B)?
A: It's an advanced large language model, fine-tuned specifically for programming tasks, built on the LLaMA architecture with 34 billion parameters to generate and analyze code with high accuracy.
Q: How does it compare to general AI models like GPT?
A: Phind Code LLaMA v2 (34B) is specialized for coding, offering superior accuracy and relevance for software development tasks compared to general-purpose AI models.
Q: What programming languages does it support?
A: While the Python-v1 version is specifically fine-tuned for Python, the model is generally designed to understand and generate code across multiple programming languages due to its robust architecture.
Q: How can I integrate Phind Code LLaMA v2 (34B) into my workflow?
A: You can integrate it via the Phind Code API, which allows you to send prompts and receive generated code or code analysis results directly into your development environment.
Q: Is the generated code always perfect and ready for production?
A: While highly accurate, it's crucial to always review and thoroughly test any AI-generated code, especially for critical applications, to ensure it meets your specific requirements and standards.
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