metadata
title: Fox1.4
emoji: 🦊
colorFrom: blue
colorTo: purple
sdk: static
app_port: 7860
pinned: false
license: apache-2.0
tags:
- transformers
- greek
- fine-tuned
- causal-lm
- qwen
- qwen2
- reasoning
model_type: qwen2
widget:
- text: What is 2+2?
- text: 'Solve this riddle: I have hands but cannot clap'
- text: Write python code to check if a number is prime
inference:
minutes: 10
🦊 Fox1.4 - Reasoning Specialist
Fox1.4 is Fox1.3's successor, trained on combined data from math, logic, knowledge, and code reasoning tasks.
Performance
Custom Benchmark (10 questions):
- ✅ All tasks: 100%
- Penguin exception logic: ✅
- $1.10 riddle: ✅
- Math (2+2, 15+27, 100/4, 7*8): ✅
- Knowledge (France, Jupiter): ✅
- Code (is_even): ✅
Estimated MMLU Score: ~40-50%
Architecture
- Base Model: Qwen2.5-0.5B (merged with LoRA adapter)
- Training: Combined data from 4 expert domains
- Parameters: ~900M
- Format: Full merged model (safetensors)
Usage
Ollama
ollama pull teolm30/fox1.4
ollama run fox1.4
Python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("teolm30/fox1.4")
tokenizer = AutoTokenizer.from_pretrained("teolm30/fox1.4")
inputs = tokenizer("What is 2+2?", return_tensors="pt")
output = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(output[0]))