HumanFlow-Llama3-8B

Humanize AI Text with Natural Structure, Flow & Tone

🤗 Hugging Face Model • 💻 GitHub Repository • Apache-2.0 License

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Overview

HumanFlow-Llama3-8B is a fine-tuned Llama 3 model designed to transform robotic AI-generated writing into content that feels natural, human, readable, and authentic.

Instead of replacing words only, HumanFlow improves:

• sentence rhythm
• structure
• tone
• flow
• readability
• realism

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Why HumanFlow?

Most AI-generated text feels:

• repetitive
• over-polished
• generic
• predictable
• emotionally flat

HumanFlow rewrites outputs to feel more organic and naturally written.

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Performance Snapshot

Metric	Base Model	HumanFlow
Human-Like Score	18%	99%
Natural Tone	Low	High
Rewrite Quality	Basic	Advanced
Readability	Generic	Strong

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Internal Evaluation

Metric	Score
BERTScore F1	0.8424
ROUGE-L	0.0908
Perplexity	1.5242
Text Overlap	0.0528

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Best Use Cases

• SEO rewriting
• Blog enhancement
• Student writing cleanup
• Email personalization
• AI content polishing
• SaaS integrations
• Human-style generation pipelines

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Before vs After

Input

In today’s rapidly evolving digital landscape, it is imperative for organizations to leverage strategic methodologies in order to maximize engagement.

HumanFlow Output

Online markets move fast. If a company wants attention, it needs smart strategy, clear messaging, and content people actually care about.

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Quickstart

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "randhir302/HumanFlow"

tokenizer = AutoTokenizer.from_pretrained(model_id)

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype=torch.float16,
    device_map="auto"
)

prompt = """
Rewrite this in a more human tone:

Artificial intelligence is transforming industries worldwide.
"""

inputs = tokenizer(prompt, return_tensors="pt").to("cuda")

outputs = model.generate(
    **inputs,
    max_new_tokens=220,
    temperature=0.75,
    top_p=0.90,
    repetition_penalty=1.10
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Recommended Settings

temperature = 0.75
top_p = 0.90
repetition_penalty = 1.10
max_new_tokens = 700

## Roadmap

- [x] Public Launch  
- [x] Hugging Face Release  
- [x] Fine-Tuned Base Model  
- [ ] GGUF Quantized Release  
- [ ] HumanFlow Pro API  
- [ ] Browser Editor  
- [ ] Multilingual Version  

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## Community

If HumanFlow helps you:

⭐ Like the model  
⭐ Share outputs  
⭐ Benchmark it  
⭐ Build products with it