language, license, library_name, tags, pipeline_tag, base_model, model-index

language	license	library_name	tags	pipeline_tag	base_model	model-index
en	apache-2.0	transformers	surfdoc qwen3 text-generation fine-tuned	text-generation	Qwen/Qwen3-8B	name results surfdoc-8b-v1

SurfDoc AI (surfdoc:8b v1)

Fine-tuned Qwen3-8B for generating structurally valid SurfDoc (.surf) documents.

Model Details

• Base model: Qwen/Qwen3-8B
• Method: QLoRA (rank 32, 87M trainable params, 1.05% of model)
• Training data: 9,241 instruction-output pairs from 26 CloudSurf repositories
• Training hardware: NVIDIA GB10 (Blackwell), 128GB unified memory
• Training time: 5.7 hours (235 steps, Flash Attention 2 enabled)
• Framework: Unsloth 2026.3.4 + PyTorch 2.10 + CUDA 12.8

What it generates

Valid SurfDoc documents with:

• YAML frontmatter (title, type, version, status, tags)
• Typed block directives (::summary, ::callout, ::data, ::action-items)
• Markdown headings and structured content
• Correct formatting and syntax

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("brady777/surfdoc-8b-v1")
tokenizer = AutoTokenizer.from_pretrained("brady777/surfdoc-8b-v1")

messages = [
    {"role": "system", "content": "You are SurfDoc AI. Generate valid SurfDoc documents."},
    {"role": "user", "content": "Create a SurfDoc plan about improving website performance"},
]
inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
outputs = model.generate(inputs.input_ids, max_new_tokens=512, temperature=0.7)
print(tokenizer.decode(outputs[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True))

Evaluation

Evaluated on 20 diverse SurfDoc generation prompts:

• Average score: 79%
• Has title: 70% | Has type: 60% | Has headings: 75%
• Uses blocks: 55% | Blocks closed: 100%
• No repetition: 95% | Good length: 100%

Note

Qwen3 is a reasoning model — outputs include <think> tags before the actual response. Strip these before display:

import re
response = re.sub(r'<think>.*?</think>', '', response, flags=re.DOTALL).strip()

Built by

CloudSurf Software LLC