Instructions to use dipeshmajithia/mirror_dolly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dipeshmajithia/mirror_dolly with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="dipeshmajithia/mirror_dolly",
	filename="mirror_dolly.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use dipeshmajithia/mirror_dolly with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf dipeshmajithia/mirror_dolly
# Run inference directly in the terminal:
llama-cli -hf dipeshmajithia/mirror_dolly

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf dipeshmajithia/mirror_dolly
# Run inference directly in the terminal:
llama-cli -hf dipeshmajithia/mirror_dolly

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 dipeshmajithia/mirror_dolly
# Run inference directly in the terminal:
./llama-cli -hf dipeshmajithia/mirror_dolly

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 dipeshmajithia/mirror_dolly
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dipeshmajithia/mirror_dolly

Use Docker

docker model run hf.co/dipeshmajithia/mirror_dolly

LM Studio
Jan
Ollama
How to use dipeshmajithia/mirror_dolly with Ollama:
```
ollama run hf.co/dipeshmajithia/mirror_dolly
```

Unsloth Studio

How to use dipeshmajithia/mirror_dolly 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 dipeshmajithia/mirror_dolly 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 dipeshmajithia/mirror_dolly to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for dipeshmajithia/mirror_dolly to start chatting

Atomic Chat new
Docker Model Runner
How to use dipeshmajithia/mirror_dolly with Docker Model Runner:
```
docker model run hf.co/dipeshmajithia/mirror_dolly
```

Lemonade

How to use dipeshmajithia/mirror_dolly with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull dipeshmajithia/mirror_dolly

Run and chat with the model

lemonade run user.mirror_dolly-{{QUANT_TAG}}

List all available models

lemonade list

🪞 Mirror Dolly (GGUF) – Model Card

🧠 Summary

Mirror Dolly is a fine-tuned assistant-style language model built on top of dipeshmajithia/MirrorCode. It was fine-tuned for 1000 iterations on the Dolly 15k dataset using LoRA, and later merged and converted to GGUF for local inference.

Mirror Dolly is designed for structured and emotionally aware assistant conversations and supports lightweight deployment with llama.cpp, ollama, or text-generation-webui.

📦 Model Overview

Base model: dipeshmajithia/MirrorCode
LoRA fine-tuning:
- Dataset: Dolly 15k
- Iterations: 1000
- Layers: 4
- Rank: 8
Merged and Converted: To GGUF via transformers + convert_hf_to_gguf.py
Quantization options: f16, q8_0, q4_0
Use cases:
- Personal assistant
- Structured explanations
- Lightweight offline inference

🛠 How to Use

▶️ With `llama.cpp`

./main -m mirror_dolly.gguf -p "Who are you?"

Downloads last month: 6

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

We're not able to determine the quantization variants.

View all variants

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for dipeshmajithia/mirror_dolly

Base model

dipeshmajithia/MirrorCode

Quantized

(1)

this model

dipeshmajithia
/

mirror_dolly

🪞 Mirror Dolly (GGUF) – Model Card

🧠 Summary

📦 Model Overview

🛠 How to Use

▶️ With `llama.cpp`

Model tree for dipeshmajithia/mirror_dolly

Dataset used to train dipeshmajithia/mirror_dolly

🪞 Mirror Dolly (GGUF) – Model Card

🧠 Summary

📦 Model Overview

🛠 How to Use

▶️ With llama.cpp

Model tree for dipeshmajithia/mirror_dolly

Dataset used to train dipeshmajithia/mirror_dolly

▶️ With `llama.cpp`