Instructions to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-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 firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF
# Run inference directly in the terminal:
llama cli -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF
# Run inference directly in the terminal:
llama cli -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

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 firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF
# Run inference directly in the terminal:
./llama-cli -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

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 firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

Use Docker

docker model run hf.co/firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

LM Studio
Jan
Ollama
How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with Ollama:
```
ollama run hf.co/firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF
```

Unsloth Studio

How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-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 firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-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 firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF to start chatting

How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with Docker Model Runner:
```
docker model run hf.co/firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF
```

Lemonade

How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

Run and chat with the model

lemonade run user.Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

Hermes Agent

How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "firmanda/Qwen3.5-0.8B-Astro-Math-LORA-R8-GGUF" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

firmanda commited on Mar 6

Commit

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@@ -212,26 +212,6 @@ qwen3.5-0.8b-astro-reasoning-v1/
 ├── qwen3.5-0.8b-astro-reasoning-v1.gguf  # GGUF format for llama.cpp
 └── training_info.md               # Detailed training logs
 ```
-## Citation
-If you use this model, please cite:
-```bibtex
-@misc{qwen3.5-0.8b-astro-reasoning-v1,
-  title={Qwen3.5-0.8B-Astro-Reasoning-v1: A Finetuned Model for Astrophysics Problem-Solving},
-  author={Your Name},
-  year={2026},
-  howpublished={HuggingFace Model Hub}
-}
-@article{qwen3.5,
-  title={Qwen3.5: Towards Native Multimodal Agents},
-  author={Qwen Team},
-  year={2026}
-}
-```
 ## Acknowledgments
 - **Base Model:** [Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) by Alibaba Cloud Qwen Team

 ├── qwen3.5-0.8b-astro-reasoning-v1.gguf  # GGUF format for llama.cpp
 └── training_info.md               # Detailed training logs
 ```
 ## Acknowledgments
 - **Base Model:** [Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) by Alibaba Cloud Qwen Team