Instructions to use DarwinAnim8or/pythia-160m-pg19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DarwinAnim8or/pythia-160m-pg19 with Transformers:

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

pipe = pipeline("text-generation", model="DarwinAnim8or/pythia-160m-pg19")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DarwinAnim8or/pythia-160m-pg19")
model = AutoModelForCausalLM.from_pretrained("DarwinAnim8or/pythia-160m-pg19")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use DarwinAnim8or/pythia-160m-pg19 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DarwinAnim8or/pythia-160m-pg19"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DarwinAnim8or/pythia-160m-pg19",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DarwinAnim8or/pythia-160m-pg19

SGLang

How to use DarwinAnim8or/pythia-160m-pg19 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/pythia-160m-pg19" \
    --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/pythia-160m-pg19",
		"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/pythia-160m-pg19" \
        --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/pythia-160m-pg19",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DarwinAnim8or/pythia-160m-pg19 with Docker Model Runner:
```
docker model run hf.co/DarwinAnim8or/pythia-160m-pg19
```

Pythia-160m-PG19

This is an experiment to see if Pythia pretrained from scratch on pg19 could work. It was trained from scratch and uses the same settings as the regular Pythia-160M. It was trained for 150,000,000 tokens of the pg19 dataset. It is possible that better results can be achieved if trained for longer, but that is not the goal of this project.

Currently I am working on creating a larger model trained on more CC0 datasets.

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pythia-160m-pg19

Pythia-160m-PG19

Dataset used to train DarwinAnim8or/pythia-160m-pg19