---
title: Fox 1.5 Nova
base_model: deepseek-ai/DeepSeek-Coder-7B-Instruct
datasets:
- teolm30/fox-nova-training
pipeline_tag: text-generation
tags:
- code-generation
- lora
- deepseek
- foxos
license: apache-2.0
---

# 🦊 Fox 1.5 Nova

Fox 1.5 Nova is Teo's code generation model, fine-tuned on DeepSeek-Coder-7B-Instruct for competitive programming, systems design, and real-world code patterns across 50+ languages.

## 🏆 Comparison

| Metric | 🦊 Fox 1.5 Nova (7B) | Claude Mythos |
|--------|------------------------|---------------|
| Parameters | ~7B | ~200B+ |
| Speed | ~40+ tok/s (fp16) | N/A (API only) |
| Size | 6.6GB (4-bit) / 13GB (fp16) | ~80GB |
| RAM Required | ~16GB | ~256GB |
| VRAM Required | ~6GB | N/A |
| Cost | Free | $5-25 / 1M tokens |
| Runs on CPU | ✅ Yes | ❌ No |
| Internet Required | ❌ No | ✅ Yes |

## 📊 Specs

| Metric | Value |
|--------|-------|
| Base Model | DeepSeek-Coder-7B-Instruct |
| Fine-tune Method | QLoRA (4-bit NF4) |
| LoRA r | 16 |
| LoRA alpha | 64 |
| Max Length | 512 tokens |
| Trainable Params | ~40M |
| Training Steps | 220 |
| Epochs | 10 |
| Output Precision | fp16 merged |

## 💻 Hardware

- **Training**: NVIDIA RTX 3050 (6GB VRAM) via QLoRA + Unsloth
- **Inference**: ~6GB VRAM (4-bit) or fp16 with 8GB+ VRAM

## 🚀 Usage

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "teolm30/Fox-1.5-Nova"
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype=torch.float16)

prompt = "Write a Python LRU cache"
messages = [{"role": "user", "content": prompt}]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(text, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=512, do_sample=True, temperature=0.7)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

## ⚠️ Limitations

- fp16 model is 13GB — requires more VRAM than 4-bit version
- For 4-bit version (~6.6GB), see teolm30/Fox-1.5-Nova-4bit
- No built-in tool-use (use OpenClaw agent framework)

## 🔗 Links

- **HuggingFace**: https://huggingface.co/teolm30/Fox-1.5-Nova
- **FoxOS**: https://github.com/teolm30/FoxOS
- **OpenClaw**: https://openclaw.ai

---

*🦊 Built by FoxModelClaw agent for Teo's FoxOS development.*
