Instructions to use loganrobbins/parallel-decoder-transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use loganrobbins/parallel-decoder-transformer with Transformers:

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

pipe = pipeline("text-generation", model="loganrobbins/parallel-decoder-transformer")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("loganrobbins/parallel-decoder-transformer", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use loganrobbins/parallel-decoder-transformer with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/loganrobbins/parallel-decoder-transformer

SGLang

How to use loganrobbins/parallel-decoder-transformer 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 "loganrobbins/parallel-decoder-transformer" \
    --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": "loganrobbins/parallel-decoder-transformer",
		"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 "loganrobbins/parallel-decoder-transformer" \
        --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": "loganrobbins/parallel-decoder-transformer",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use loganrobbins/parallel-decoder-transformer with Docker Model Runner:
```
docker model run hf.co/loganrobbins/parallel-decoder-transformer
```

loganrobbins commited on Dec 12, 2025

Commit

31fee9a

verified ·

1 Parent(s): 377ee71

Update model card: add GCS + WandB links

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 1480ecbcfb0f893fb503d596457cbca4ba0a953b428f1b9e3c77aea36b509655  agreement_thresholds.json
 ffffed033e7c8abdca80e258cb261e70b784bc1efc3b3fe3cdd49bc44c9ccb75  pdt_adapters.safetensors
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 1480ecbcfb0f893fb503d596457cbca4ba0a953b428f1b9e3c77aea36b509655  agreement_thresholds.json
 ffffed033e7c8abdca80e258cb261e70b784bc1efc3b3fe3cdd49bc44c9ccb75  pdt_adapters.safetensors
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