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Model: teolm30/fox1.4
Source: Original Platform

README.md

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+---
+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]))
+```
+
+## 🤖 Run with Ollama
+
+```bash
+ollama run hf.co/teolm30/fox1.4
+```