Instructions to use teolm30/fox1.4-high-reasoning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use teolm30/fox1.4-high-reasoning with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="teolm30/fox1.4-high-reasoning",
	filename="fox1.4-high-reasoning.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 teolm30/fox1.4-high-reasoning with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf teolm30/fox1.4-high-reasoning
# Run inference directly in the terminal:
llama-cli -hf teolm30/fox1.4-high-reasoning

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf teolm30/fox1.4-high-reasoning
# Run inference directly in the terminal:
llama-cli -hf teolm30/fox1.4-high-reasoning

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 teolm30/fox1.4-high-reasoning
# Run inference directly in the terminal:
./llama-cli -hf teolm30/fox1.4-high-reasoning

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 teolm30/fox1.4-high-reasoning
# Run inference directly in the terminal:
./build/bin/llama-cli -hf teolm30/fox1.4-high-reasoning

Use Docker

docker model run hf.co/teolm30/fox1.4-high-reasoning

LM Studio
Jan
Ollama
How to use teolm30/fox1.4-high-reasoning with Ollama:
```
ollama run hf.co/teolm30/fox1.4-high-reasoning
```

Unsloth Studio

How to use teolm30/fox1.4-high-reasoning 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 teolm30/fox1.4-high-reasoning 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 teolm30/fox1.4-high-reasoning to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for teolm30/fox1.4-high-reasoning to start chatting

Docker Model Runner
How to use teolm30/fox1.4-high-reasoning with Docker Model Runner:
```
docker model run hf.co/teolm30/fox1.4-high-reasoning
```

Lemonade

How to use teolm30/fox1.4-high-reasoning with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull teolm30/fox1.4-high-reasoning

Run and chat with the model

lemonade run user.fox1.4-high-reasoning-{{QUANT_TAG}}

List all available models

lemonade list

fox1.4-high-reasoning / README.md

teolm30

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metadata

license: apache-2.0
tags:
  - greek
  - fine-tuned
  - causal-lm
  - qwen
  - qwen2
base_model: teolm30/fox1.3
inference:
  parameters:
    temperature: 0.7
    max_new_tokens: 256
widget:
  - text: Τι είναι η τεχνητή νοημοσύνη;
  - text: Πες μου για την Ελλάδα
  - text: Γράψε ένα ποίημα για τον ήλιο
model_type: qwen2

Fox 1.4 High Reasoning

A Greek fine-tuned version of Fox 1.3, a Qwen2.5-1B-Instruct based model.

Training

Method: QLoRA (4-bit quantization)
Dataset: Custom Greek conversation dataset (20 conversations)
Epochs: 3
Loss: 3.26 → 0.79
Hardware: NVIDIA RTX 3050 (6GB VRAM)
LoRA rank: 8, alpha: 16

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("teolm30/fox1.4-high-reasoning", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("teolm30/fox1.4-high-reasoning", trust_remote_code=True)

messages = [{"role": "user", "content": "Τι είναι η τεχνητή νοημοσύνη;"}]
input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt")
output = model.generate(input_ids, max_new_tokens=256)
print(tokenizer.decode(output[0]))

Greek Language Support

Fine-tuned for Greek language — grammar, vocabulary, natural conversation, and technical topics in Greek.

Previous Versions

Fox 1.3 — base model
Fox 1.0 — original model

🤖 Run with Ollama

ollama run hf.co/teolm30/fox1.4-high-reasoning