Instructions to use DarwinAnim8or/GPT-NoSleep-1.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DarwinAnim8or/GPT-NoSleep-1.5b with Transformers:

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

pipe = pipeline("text-generation", model="DarwinAnim8or/GPT-NoSleep-1.5b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DarwinAnim8or/GPT-NoSleep-1.5b")
model = AutoModelForCausalLM.from_pretrained("DarwinAnim8or/GPT-NoSleep-1.5b", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DarwinAnim8or/GPT-NoSleep-1.5b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DarwinAnim8or/GPT-NoSleep-1.5b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DarwinAnim8or/GPT-NoSleep-1.5b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DarwinAnim8or/GPT-NoSleep-1.5b

SGLang

How to use DarwinAnim8or/GPT-NoSleep-1.5b 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 "DarwinAnim8or/GPT-NoSleep-1.5b" \
    --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": "DarwinAnim8or/GPT-NoSleep-1.5b",
		"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 "DarwinAnim8or/GPT-NoSleep-1.5b" \
        --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": "DarwinAnim8or/GPT-NoSleep-1.5b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DarwinAnim8or/GPT-NoSleep-1.5b with Docker Model Runner:
```
docker model run hf.co/DarwinAnim8or/GPT-NoSleep-1.5b
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

GPT-NoSleep-1.5b

This is the largest release of GPT-NoSleep; a finetuned version of GPT2-XL on the 'reddit-nosleep-posts' dataset. Smaller releases include:

GPT-NoSleep-355m

And the accompanying prompt generator can be found here:

Training Procedure

This was trained on the 'reddt-nosleep-posts' dataset, on Google Colab. This model was trained for 2 epochs with learning rate 1e-2. Special thanks for Skyler for helping to train this large of a model!

Biases & Limitations

This likely contains the same biases and limitations as the original GPT2 that it is based on, and additionally heavy biases from the dataset. It can generate output that is not meant for all audiences, seeing as it's purpose is to generate horror stories.

Intended Use

This model is meant for fun, nothing else.

Downloads last month: 19

Safetensors

Model size

2B params

Tensor type

F16

BOOL

Model tree for DarwinAnim8or/GPT-NoSleep-1.5b

Quantizations

2 models

DarwinAnim8or
/

GPT-NoSleep-1.5b

GPT-NoSleep-1.5b

Training Procedure

Biases & Limitations

Intended Use

Model tree for DarwinAnim8or/GPT-NoSleep-1.5b

Dataset used to train DarwinAnim8or/GPT-NoSleep-1.5b

Space using DarwinAnim8or/GPT-NoSleep-1.5b 1