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Models/Phi-3.5-Medical-GGUF-Q4_K_M
Hugging Face CommunityOpen Weights

Phi-3.5-Medical-GGUF-Q4_K_M

Specialized Domain LLM โ€ข Released 2024-11-12 โ€ข Last Verified 2025-02-01

Try PlaygroundDocs

Phi-3.5-Medical-GGUF-Q4_K_M - Fine-tuned and quantized Medical domain model variant optimized for fast local host inference.

Context Window32k-128k
LicenseApache-2.0 / Community Open Source
Deployment
Local Model
API AvailableNo
๐Ÿ’ก

Plain English Summary (What is this model & who is it for?)

Think of Phi-3.5-Medical-GGUF-Q4_K_M as a versatile AI assistant for writing, research, and brainstorming. It helps you draft emails, write essays, summarize long articles, and generate creative ideas on any topic.

๐Ÿ’ก Real-World Use Cases & Practical Examples

โœ๏ธ Email & Article Drafting: Draft professional emails, blog posts, and press releases in seconds.
๐Ÿ“š Long Document Summarization: Condense 50-page PDF reports into actionable bullet points.
๐Ÿ’ก Brainstorming & Strategy: Generate marketing ideas, product names, and event outlines.
๐ŸŽ“ Learning Partner: Ask questions and get step-by-step explanations on any topic.

๐Ÿš€ How to Run & Use This Model (Step-by-Step Guide)

Simple setup instructions for everyday users and developers.

1

Download a One-Click App (No Coding Required)

Download a free local AI launcher like LM Studio (lmstudio.ai) or Ollama (ollama.com) on your Mac, Windows, or Linux PC.

2

Load the Model

In LM Studio, search for "Phi-3.5-Medical-GGUF-Q4_K_M". In Ollama, open your terminal and run "ollama run phi-3-5-medical-gguf-q4-k-m".

3

Start Chatting or Generating

Type your text instructions or upload files into the app. The AI runs 100% privately on your hardware without internet requirement!

4

Developer API Integration

Developers can integrate Phi-3.5-Medical-GGUF-Q4_K_M directly via Python (using Hugging Face transformers/diffusers) or connect via local OpenAI-compatible REST server (http://localhost:11434).

Benchmark Performance

Medical Domain Score85

Hardware Requirements for Local Running

Requires 4GB-8GB VRAM

Strengths

  • โ€ขHigh accuracy
  • โ€ขFast inference

Limitations & Weaknesses

  • โ€ขClosed source API
Integration Code (text-chat)
import openai

client = openai.OpenAI()

response = client.chat.completions.create(
    model="phi-3-5-medical-gguf-q4-k-m",
    messages=[
        {"role": "system", "content": "You are an expert AI assistant."},
        {"role": "user", "content": "Explain quantum computing in 2 sentences."}
    ]
)

print(response.choices[0].message.content)

Pricing Overview

Free Open Source (Hugging Face / Ollama)

Prices subject to provider tiers and volume discounts. Check documentation for current token rates.

Model Tags

#medical#ollama#huggingface#quantized#local

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