title, base_model, datasets, pipeline_tag, tags, license

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

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

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