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