Instructions to use netwninja82/holodeck-phi35-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use netwninja82/holodeck-phi35-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf netwninja82/holodeck-phi35-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf netwninja82/holodeck-phi35-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf netwninja82/holodeck-phi35-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf netwninja82/holodeck-phi35-gguf:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf netwninja82/holodeck-phi35-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf netwninja82/holodeck-phi35-gguf:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf netwninja82/holodeck-phi35-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf netwninja82/holodeck-phi35-gguf:Q4_K_M

Use Docker

docker model run hf.co/netwninja82/holodeck-phi35-gguf:Q4_K_M

LM Studio
Jan
Ollama
How to use netwninja82/holodeck-phi35-gguf with Ollama:
```
ollama run hf.co/netwninja82/holodeck-phi35-gguf:Q4_K_M
```

Unsloth Studio

How to use netwninja82/holodeck-phi35-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for netwninja82/holodeck-phi35-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for netwninja82/holodeck-phi35-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for netwninja82/holodeck-phi35-gguf to start chatting

Docker Model Runner
How to use netwninja82/holodeck-phi35-gguf with Docker Model Runner:
```
docker model run hf.co/netwninja82/holodeck-phi35-gguf:Q4_K_M
```

Lemonade

How to use netwninja82/holodeck-phi35-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull netwninja82/holodeck-phi35-gguf:Q4_K_M

Run and chat with the model

lemonade run user.holodeck-phi35-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

Holodeck Phi-3.5 (LoRA Fine-Tuned)

Phi-3.5-mini-instruct fine-tuned on VMware Holodeck documentation using LoRA.

Quick Start with Ollama or Docker model

# Download and run directly from HF
ollama run hf.co/netwninja82/holodeck-phi35-gguf:Q4_K_M

OR

docker model run hf.co/netwninja82/holodeck-phi35-gguf:Q4_K_M

Model Details

Base model: microsoft/Phi-3.5-mini-instruct
Fine-tuning: LoRA (rank 64, alpha 128)
Quantization: Q4_K_M
Training data: VMware Holodeck documentation (RAG-style)

Key Facts

VMware Holodeck is PUBLICLY AVAILABLE (not internal-only)
Official website: https://vmware.github.io/Holodeck/
Downloads: https://vmware.github.io/Holodeck/downloads/

Best Usage

For best accuracy, use with RAG retrieval to provide context before answering.

Downloads last month: 11

GGUF

Model size

4B params

Architecture

phi3

Hardware compatibility

4-bit

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Model tree for netwninja82/holodeck-phi35-gguf

Base model

microsoft/Phi-3.5-mini-instruct

Quantized

(192)

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