📦 Multi-Model Repository

Find descriptions and details about various AI models, including their capabilities, use cases, and specifications.

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🚀 Models Overview

DeepSeek R1

📌 Description:
Distilled LLaMA by DeepSeek, fast and optimized for real-world tasks.

📂 Model File: ai/deepseek-r1-distill-llama.md

URLs:

• https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B
• https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-70B

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Gemma 3

📌 Description:
Google's latest Gemma, small yet strong for chat and generation

📂 Model File: ai/gemma3.md

URLs:

• https://huggingface.co/google/gemma-3-4b-it

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Llama 3.1

📌 Description:
Meta's LLaMA 3.1: Chat-focused, benchmark-strong, multilingual-ready.

📂 Model File: ai/llama3.1.md

URLs:

• https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct

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Llama 3.2

📌 Description:
Solid LLaMA 3 update, reliable for coding, chat, and Q&A tasks.

📂 Model File: ai/llama3.2.md

URL:

• https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct
• https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct

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Llama 3.3

📌 Description:
Newest LLaMA 3 release with improved reasoning and generation quality.

📂 Model File: ai/llama3.3.md

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Mistral 7b

📌 Description:
A fast and powerful 7B parameter model excelling in reasoning, code, and math.

📂 Model File: ai/mistral.md

URLs:

• https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3

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Mistral Nemo

📌 Description:
Mistral-Nemo-Instruct-2407 is an instruct fine-tuned large language model developed by Mistral AI and NVIDIA.

📂 Model File: ai/mistral-nemo.md

URLs:

• https://huggingface.co/mistralai/Mistral-Nemo-Instruct-2407

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mxbai-embed-large

📌 Description:
A state-of-the-art English language embedding model developed by Mixedbread AI.

📂 Model File: ai/mxbai-embed-large.md

URLs:

• https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1

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Phi-4

📌 Description:
Microsoft's compact model, surprisingly capable at reasoning and code.

📂 Model File: ai/phi4.md

URLs:

• https://huggingface.co/microsoft/phi-4

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Qwen 2.5

📌 Description:
Versatile Qwen update with better language skills and wider support.

📂 Model File: ai/qwen2.5.md

URLs:

• https://huggingface.co/Qwen/Qwen2.5-7B-Instruct

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QwQ

📌 Description:
Experimental Qwen variant—lean, fast, and a bit mysterious.

📂 Model File: ai/qwq.md

URLs:

• https://huggingface.co/Qwen/QwQ-32B

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SmolLM 2

📌 Description:
A compact language model, designed to run efficiently on-device while performing a wide range of language tasks

📂 Model File: ai/smollm2.md

URLs:

• https://huggingface.co/HuggingFaceTB/SmolLM2-360M-Instruct
• https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct

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🔧 CLI Usage

The model-cards-cli tool provides commands to inspect and update model information:

Inspect Command

# Basic inspection
make inspect REPOSITORY=ai/smollm2

# Inspect specific tag
make inspect REPOSITORY=ai/smollm2 TAG=360M-Q4_K_M

# Show all metadata
make inspect REPOSITORY=ai/smollm2 OPTIONS="--all"

Update Command

# Update all models
make run

# Update specific model
make run-single MODEL=smollm2.md

Upload Overview Command

# Upload a single overview to Docker Hub
make -C tools/model-cards-cli upload-overview FILE=ai/llama3.1.md REPO=ai/llama3 USERNAME=your_username TOKEN=your_pat_here

# Upload all overviews in the ai/ folder to their corresponding repositories
./tools/upload-all-overviews.sh your_username your_pat_here

Available Options

Inspect Command Options

• REPOSITORY: (Required) The repository to inspect (e.g., ai/smollm2)
• TAG: (Optional) Specific tag to inspect (e.g., 360M-Q4_K_M)
• OPTIONS: (Optional) Additional options:
  • --all: Show all metadata fields
  • --log-level: Set log level (debug, info, warn, error)

Update Command Options

• MODEL: (Required for run-single) Specific model file to update (e.g., ai/smollm2.md)
• --log-level: Set log level (debug, info, warn, error)

Upload Overview Options

• FILE: (Required) Path to the markdown file containing the overview content
• REPO: (Required) Repository to upload the overview to (format: namespace/repository)
• USERNAME: (Required) Docker Hub username
• TOKEN: (Required) Personal Access Token (PAT)