Instructions to use Hengchang-Liu/D3LM-scratch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Hengchang-Liu/D3LM-scratch with Transformers:

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

pipe = pipeline("text-generation", model="Hengchang-Liu/D3LM-scratch", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM

tokenizer = AutoTokenizer.from_pretrained("Hengchang-Liu/D3LM-scratch", trust_remote_code=True)
model = AutoModelForMaskedLM.from_pretrained("Hengchang-Liu/D3LM-scratch", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Hengchang-Liu/D3LM-scratch with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Hengchang-Liu/D3LM-scratch"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Hengchang-Liu/D3LM-scratch",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Hengchang-Liu/D3LM-scratch

SGLang

How to use Hengchang-Liu/D3LM-scratch 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 "Hengchang-Liu/D3LM-scratch" \
    --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": "Hengchang-Liu/D3LM-scratch",
		"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 "Hengchang-Liu/D3LM-scratch" \
        --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": "Hengchang-Liu/D3LM-scratch",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Hengchang-Liu/D3LM-scratch with Docker Model Runner:
```
docker model run hf.co/Hengchang-Liu/D3LM-scratch
```

D3LM-scratch

Commit History

Update README.md

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Hengchang-Liu

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Update README.md

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Upload folder using huggingface_hub

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Hengchang-Liu commited on Mar 2

Upload folder using huggingface_hub

f03ec3e
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Hengchang-Liu commited on Mar 2

Upload folder using huggingface_hub

27314ee
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Hengchang-Liu commited on Mar 2

initial commit

41243f2
verified

Hengchang-Liu commited on Mar 2

Commit History

Update README.md 4c0d92b verified

Improve model card metadata and add paper link (#1) 0c5a43f

Update README.md 2a8a8f2 verified

Upload folder using huggingface_hub 277ff36 verified

Upload folder using huggingface_hub 04bdbad verified

Upload folder using huggingface_hub 8b2f1c2 verified

Upload folder using huggingface_hub f03ec3e verified

Upload folder using huggingface_hub 27314ee verified

initial commit 41243f2 verified

Update README.md

4c0d92b
verified

Improve model card metadata and add paper link (#1)

0c5a43f

Update README.md

2a8a8f2
verified

Upload folder using huggingface_hub

277ff36
verified

Upload folder using huggingface_hub

04bdbad
verified

Upload folder using huggingface_hub

8b2f1c2
verified

Upload folder using huggingface_hub

f03ec3e
verified

Upload folder using huggingface_hub

27314ee
verified

initial commit

41243f2
verified