Instructions to use Yemen-JPT/WebProcessor-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Yemen-JPT/WebProcessor-v1 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Yemen-JPT/WebProcessor-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Yemen-JPT/WebProcessor-v1")
model = AutoModelForCausalLM.from_pretrained("Yemen-JPT/WebProcessor-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Yemen-JPT/WebProcessor-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Yemen-JPT/WebProcessor-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Yemen-JPT/WebProcessor-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Yemen-JPT/WebProcessor-v1

SGLang

How to use Yemen-JPT/WebProcessor-v1 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Yemen-JPT/WebProcessor-v1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Yemen-JPT/WebProcessor-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Yemen-JPT/WebProcessor-v1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Yemen-JPT/WebProcessor-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Yemen-JPT/WebProcessor-v1 with Docker Model Runner:
```
docker model run hf.co/Yemen-JPT/WebProcessor-v1
```

WebProcessor-v1

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---
pipeline_tag: text-generation
library_name: transformers
tags:
  - yemenjpt
  - osint
  - journalism
  - arabic
  - safetensors
  - qwen
license: apache-2.0
language:
  - ar
  - en
base_model: tomvaillant/qwen-3.5-process-web
---

# YemenJPT-WebProcessor-v1

> **معالج الويب - لاستخراج وتحليل محتوى المواقع**

<div dir="rtl">

## الوصف
معالج الويب - لاستخراج وتحليل محتوى المواقع. هذا النموذج/القاعدة جزء من مجموعة YemenJPT المخصصة لدعم الصحافة الاستقصائية اليمنية.

## الروابط
- [المستودع على HuggingFace](https://huggingface.co/Yemen-JPT/OSINT-Web)
- [منظومة YemenJPT](https://huggingface.co/Yemen-JPT)
- [الموقع الرسمي](http://yemenjpt.raidan.pro)
- [Ollama](https://ollama.com/YemenJPT)
- [RaidanPro](https://raidan.pro)
- [بيت الصحافة](https://ph-ye.org)

## التحميل
```bash
# عبر HuggingFace Hub
git lfs clone https://huggingface.co/Yemen-JPT/OSINT-Web

# أو عبر pip (للنماذج)
pip install huggingface-hub
huggingface-cli download Yemen-JPT/OSINT-Web
```

## الترخيص
هذا العمل متاح تحت رخصة Apache 2.0 (للنماذج) أو CC-BY-4.0 (لقواعد البيانات).

</div>

---

<div align="center" dir="rtl">
  <b>YemenJPT</b> &mdash; تمكين الصحافة اليمنية بالذكاء الاصطناعي<br>
  طُوّر بواسطة <a href="https://raidan.pro">RaidanPro</a> بالتعاون مع <a href="https://ph-ye.org">بيت الصحافة - Press House</a><br>
  <a href="http://yemenjpt.raidan.pro">الموقع الرسمي</a> &bull;
  <a href="https://facebook.com/YemenJPT">فيسبوك</a> &bull;
  <a href="https://linkedin.com/YemenJPT">لينكدإن</a> &bull;
  <a href="https://youtube.com/YemenJPT">يوتيوب</a> &bull;
  <a href="https://huggingface.co/Yemen-JPT">HuggingFace</a> &bull;
  <a href="https://ollama.com/YemenJPT">Ollama</a><br>
  <a href="mailto:yemenjpt@raidan.pro">yemenjpt@raidan.pro</a>
</div>

---

## YemenJPT-WebProcessor-v1

> **Web processor for extracting and analyzing website content**

<div>

## Description
Web processor for extracting and analyzing website content. This model/dataset is part of the YemenJPT collection dedicated to supporting Yemeni investigative journalism.

## Links
- [HuggingFace Repository](https://huggingface.co/Yemen-JPT/OSINT-Web)
- [YemenJPT Website](http://yemenjpt.raidan.pro)
- [Ollama](https://ollama.com/YemenJPT)
- [RaidanPro](https://raidan.pro)
- [Press House](https://ph-ye.org)

## Download
```bash
# Via HuggingFace Hub
git lfs clone https://huggingface.co/Yemen-JPT/OSINT-Web

# Or via pip (for models)
pip install huggingface-hub
huggingface-cli download Yemen-JPT/OSINT-Web
```

## License
This work is licensed under Apache 2.0 (for models) or CC-BY-4.0 (for datasets).

</div>