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

771b6cb

verified ·

1 Parent(s): b6a24df

Model card: fix GitHub URL (logan-robbins)

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -340,7 +340,7 @@ uv run python scripts/pretty_notes_artifact.py survey_200141_ff0a0b4f.json
 ## How to use
 1. Install the reference implementation (runtime + scripts):
-   - `https://github.com/ljrweb-self/parallel-decoder-transformer`
 2. Download the base trunk model (`openai/gpt-oss-20b`) via Hugging Face (or provide a local path).
 3. Download the adapter checkpoint from this repo and point `configs/gpt_oss_transfer_production.yaml` (or CLI flags) at it.
@@ -399,4 +399,4 @@ This layout is required to support the **teacher→student curriculum** describe
 - **This repo (adapters + artifacts)**: MIT.
 - **Base model**: `openai/gpt-oss-20b` is licensed under Apache-2.0 on Hugging Face (also see its `USAGE_POLICY` there).
-- **Reference implementation**: MIT at `https://github.com/ljrweb-self/parallel-decoder-transformer`.

 ## How to use
 1. Install the reference implementation (runtime + scripts):
+   - `https://github.com/logan-robbins/parallel-decoder-transformer`
 2. Download the base trunk model (`openai/gpt-oss-20b`) via Hugging Face (or provide a local path).
 3. Download the adapter checkpoint from this repo and point `configs/gpt_oss_transfer_production.yaml` (or CLI flags) at it.
 - **This repo (adapters + artifacts)**: MIT.
 - **Base model**: `openai/gpt-oss-20b` is licensed under Apache-2.0 on Hugging Face (also see its `USAGE_POLICY` there).
+- **Reference implementation**: MIT at `https://github.com/logan-robbins/parallel-decoder-transformer`.