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

377ee71

verified ·

1 Parent(s): 4600161

Update model card: add GCS + WandB links

Browse files

Files changed (1) hide show

README.md +13 -0

README.md CHANGED Viewed

@@ -35,6 +35,19 @@ Autoregressive decoding in Large Language Models (LLMs) is inherently sequential
 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.
 ## Citation
 ```bibtex

 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.
+## Artifacts (public GCS)
+The complete training artifacts and dataset archives are mirrored publicly in GCS:
+- **Bucket root:** `https://storage.googleapis.com/parallel-decoder-transformer/`
+- **Upload manifest (full listing):** `https://storage.googleapis.com/parallel-decoder-transformer/UPLOAD_MANIFEST.md`
+- **Training checkpoints:** `https://storage.googleapis.com/parallel-decoder-transformer/checkpoints/gpt-oss-8xH100-50000steps/`
+- **Dataset archives:** `https://storage.googleapis.com/parallel-decoder-transformer/data/archives/`
+## Training logs (Weights & Biases)
+- **WandB run:** `https://wandb.ai/ljrweb-self/parallel-decoder-transformer/runs/fmuea63a`
 ## Citation
 ```bibtex