Instructions to use imocha-ai-org/job-description-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use imocha-ai-org/job-description-generator with Transformers:

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

pipe = pipeline("text-generation", model="imocha-ai-org/job-description-generator")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("imocha-ai-org/job-description-generator")
model = AutoModelForCausalLM.from_pretrained("imocha-ai-org/job-description-generator")
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

vLLM

How to use imocha-ai-org/job-description-generator with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/imocha-ai-org/job-description-generator

SGLang

How to use imocha-ai-org/job-description-generator 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 "imocha-ai-org/job-description-generator" \
    --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": "imocha-ai-org/job-description-generator",
		"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 "imocha-ai-org/job-description-generator" \
        --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": "imocha-ai-org/job-description-generator",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use imocha-ai-org/job-description-generator with Docker Model Runner:
```
docker model run hf.co/imocha-ai-org/job-description-generator
```

SSF-Aligned Job Description Generator

Generate recruiter-ready, SSF-compliant job descriptions for the Singapore workforce in seconds.

This model is developed by iMocha to generate Singapore Skills Framework (SSF)–aligned, structured job descriptions suitable for enterprise HR platforms, skills intelligence systems, and talent assessment workflows.

It ensures consistent structure, professional tone, and regulatory alignment, reducing manual effort for HR teams and recruiters.

Why This Model?

Designed specifically for Singapore Skills Framework (SSF) compliance
Produces structured, recruiter-ready outputs without prompt engineering
Demonstrates excellent semantic accuracy (BERTScore F1: 0.91+)
Ensures 100% SSF section completeness
Suitable for enterprise-scale HR and talent intelligence workflows

Model Overview

Model Family: LLaMA-3.2-3B-Instruct
Owner: iMocha
Primary Task: SSF-aligned job description generation
Language: English
Domain Focus: Singapore workforce and skills taxonomy

Key Capabilities

Generates structured, recruiter-ready job descriptions
Ensures 100% compliance with SSF section requirements
Produces professionally written, non-generic content
Adapts to different roles, sectors, tracks, and career levels
Suitable for enterprise HR and talent intelligence use cases

Performance Highlights

Metric	Score	Interpretation
ROUGE-1	0.5743	Strong coverage of key job-related terms
ROUGE-2	0.3334	Good phrase-level accuracy
ROUGE-L	0.4335	Consistent structural similarity
BERTScore (F1)	0.9170	Excellent semantic alignment
SSF Structure Compliance	100%	All required SSF sections present ✓

Summary:
The model demonstrates high semantic accuracy, strong content alignment, and perfect structural reliability, making it suitable for production HR workflows.

Copy-Paste Prompt

Generate a concise, recruiter-ready, SSF-aligned job description.

Role:
Sector:
Track:
Career Level:

Downloads last month: 10

Safetensors

Model size

3B params

Tensor type

F16

Model tree for imocha-ai-org/job-description-generator

Base model

meta-llama/Llama-3.2-3B-Instruct

Finetuned

(1599)

this model