| --- |
| 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 |
| |
| ```bash |
| ollama pull teolm30/fox1.4 |
| ollama run fox1.4 |
| ``` |
| |
| ### Python |
| |
| ```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])) |
| ``` |
| |
