初始化项目，由ModelHub XC社区提供模型
Model: randhir302/HumanFlow Source: Original Platform
This commit is contained in:
ModelHub XC
200
README.md
Normal file
200
README.md
Normal file
@@ -0,0 +1,200 @@
|
||||
---
|
||||
language:
|
||||
- en
|
||||
license: apache-2.0
|
||||
base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
|
||||
library_name: transformers
|
||||
pipeline_tag: text-generation
|
||||
|
||||
tags:
|
||||
- text-generation
|
||||
- llama3
|
||||
- humanizer
|
||||
- rewriting
|
||||
- conversational
|
||||
- merged
|
||||
- sft
|
||||
- editorial
|
||||
|
||||
widget:
|
||||
- text: "Rewrite this in a more human tone: The system is functioning correctly."
|
||||
example_title: "Smooth System"
|
||||
|
||||
- text: "Rewrite this in a more human tone: The implementation has been completed successfully."
|
||||
example_title: "Successful Setup"
|
||||
|
||||
- text: "Rewrite this in a more human tone: The user is advised to proceed with caution."
|
||||
example_title: "Friendly Warning"
|
||||
|
||||
model-index:
|
||||
- name: HumanFlow-Llama3-8B
|
||||
results:
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
name: Internal Evaluation Suite
|
||||
type: custom
|
||||
metrics:
|
||||
- type: BERTScore F1
|
||||
value: 0.8424
|
||||
- type: ROUGE-L
|
||||
value: 0.0908
|
||||
- type: Perplexity
|
||||
value: 1.5242
|
||||
- type: Text Overlap
|
||||
value: 0.0528
|
||||
---
|
||||
|
||||
<p align="center">
|
||||
<img src="https://huggingface.co/randhir302/HumanFlow/resolve/main/humanflow_logofinal.png" width="240" height="240">
|
||||
</p>
|
||||
|
||||
# HumanFlow-Llama3-8B
|
||||
|
||||
### Humanize AI Text with Natural Structure, Flow & Tone
|
||||
|
||||
[🤗 Hugging Face Model](https://huggingface.co/randhir302/HumanFlow) •
|
||||
[💻 GitHub Repository](https://github.com/iamhero2709/HumanFlow) •
|
||||
Apache-2.0 License
|
||||
|
||||
---
|
||||
|
||||
## 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
|
||||
|
||||
---
|
||||
|
||||
## Why HumanFlow?
|
||||
|
||||
Most AI-generated text feels:
|
||||
|
||||
- repetitive
|
||||
- over-polished
|
||||
- generic
|
||||
- predictable
|
||||
- emotionally flat
|
||||
|
||||
HumanFlow rewrites outputs to feel more organic and naturally written.
|
||||
|
||||
---
|
||||
|
||||
## Performance Snapshot
|
||||
|
||||
| Metric | Base Model | HumanFlow |
|
||||
|--------|-----------|----------|
|
||||
| Human-Like Score | 18% | **99%** |
|
||||
| Natural Tone | Low | **High** |
|
||||
| Rewrite Quality | Basic | **Advanced** |
|
||||
| Readability | Generic | **Strong** |
|
||||
|
||||
---
|
||||
|
||||
## Internal Evaluation
|
||||
|
||||
| Metric | Score |
|
||||
|--------|------|
|
||||
| BERTScore F1 | **0.8424** |
|
||||
| ROUGE-L | **0.0908** |
|
||||
| Perplexity | **1.5242** |
|
||||
| Text Overlap | **0.0528** |
|
||||
|
||||
---
|
||||
|
||||
## Best Use Cases
|
||||
|
||||
- SEO rewriting
|
||||
- Blog enhancement
|
||||
- Student writing cleanup
|
||||
- Email personalization
|
||||
- AI content polishing
|
||||
- SaaS integrations
|
||||
- Human-style generation pipelines
|
||||
|
||||
---
|
||||
|
||||
## 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.
|
||||
|
||||
---
|
||||
|
||||
## Quickstart
|
||||
|
||||
```python
|
||||
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
|
||||
|
||||
```python
|
||||
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
|
||||
|
||||
---
|
||||
|
||||
## Community
|
||||
|
||||
If HumanFlow helps you:
|
||||
|
||||
⭐ Like the model
|
||||
⭐ Share outputs
|
||||
⭐ Benchmark it
|
||||
⭐ Build products with it
|
||||
|
||||
Reference in New Issue
Block a user