Instructions to use CodeferSystem/GPT2-Hacker-password-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CodeferSystem/GPT2-Hacker-password-generator with Transformers:

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

pipe = pipeline("text-generation", model="CodeferSystem/GPT2-Hacker-password-generator")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("CodeferSystem/GPT2-Hacker-password-generator")
model = AutoModelForCausalLM.from_pretrained("CodeferSystem/GPT2-Hacker-password-generator")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use CodeferSystem/GPT2-Hacker-password-generator with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CodeferSystem/GPT2-Hacker-password-generator"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CodeferSystem/GPT2-Hacker-password-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/CodeferSystem/GPT2-Hacker-password-generator

SGLang

How to use CodeferSystem/GPT2-Hacker-password-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 "CodeferSystem/GPT2-Hacker-password-generator" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CodeferSystem/GPT2-Hacker-password-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "CodeferSystem/GPT2-Hacker-password-generator" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CodeferSystem/GPT2-Hacker-password-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use CodeferSystem/GPT2-Hacker-password-generator with Docker Model Runner:
```
docker model run hf.co/CodeferSystem/GPT2-Hacker-password-generator
```

CodeferSystem commited on Aug 21, 2025

Commit

38c9b8b

verified ·

1 Parent(s): 8da5163

Update README.md

Browse files

- Updated model loading due to username change.
- Updated incorrect information in the number of dataset examples.

Files changed (1) hide show

README.md +5 -2

README.md CHANGED Viewed

@@ -3,6 +3,9 @@ license: apache-2.0
 language:
 - en
 pipeline_tag: text-generation
 ---
 # GPT-2 Hacker password generator.
 This model can generate hacker passwords.
@@ -16,7 +19,7 @@ Loss: 0.519600
 Fine-tuning time: almost 34:39 on Nvidia Geforce RTX 4060 8 GB GPU (laptop)
-Fine-tuned on 3674.21 examples of 128 tokens.
 # Using the model
 Use this code:
@@ -25,7 +28,7 @@ Use this code:
 from transformers import GPT2Tokenizer, GPT2LMHeadModel
 import torch
-model_name = "Codefer/GPT2-Hacker-password-generator"
 # Load the pre-trained GPT-2 model and tokenizer from the specified directory
 tokenizer = GPT2Tokenizer.from_pretrained(model_name)  # Load standard GPT-2 tokenizer

 language:
 - en
 pipeline_tag: text-generation
+base_model:
+- openai-community/gpt2
+library_name: transformers
 ---
 # GPT-2 Hacker password generator.
 This model can generate hacker passwords.
 Fine-tuning time: almost 34:39 on Nvidia Geforce RTX 4060 8 GB GPU (laptop)
+Fine-tuned on 20k examples of 128 tokens.
 # Using the model
 Use this code:
 from transformers import GPT2Tokenizer, GPT2LMHeadModel
 import torch
+model_name = "CodeferSystem/GPT2-Hacker-password-generator"
 # Load the pre-trained GPT-2 model and tokenizer from the specified directory
 tokenizer = GPT2Tokenizer.from_pretrained(model_name)  # Load standard GPT-2 tokenizer