Instructions to use danielhanchen/vllm_upload with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use danielhanchen/vllm_upload with Transformers:

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

pipe = pipeline("text-generation", model="danielhanchen/vllm_upload")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("danielhanchen/vllm_upload")
model = AutoModelForCausalLM.from_pretrained("danielhanchen/vllm_upload", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use danielhanchen/vllm_upload with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/danielhanchen/vllm_upload

SGLang

How to use danielhanchen/vllm_upload 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 "danielhanchen/vllm_upload" \
    --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": "danielhanchen/vllm_upload",
		"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 "danielhanchen/vllm_upload" \
        --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": "danielhanchen/vllm_upload",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Unsloth Desktop
Docker Model Runner
How to use danielhanchen/vllm_upload with Docker Model Runner:
```
docker model run hf.co/danielhanchen/vllm_upload
```

vllm_upload

Commit History

Jun 15, 2025

06:11
Adding `safetensors` variant of this model⁠

SFconvertbot

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Feb 4, 2024

15:54
Upload MistralForCausalLM

danielhanchen

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15:49
Upload tokenizer

danielhanchen

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336f2b5
15:48
Upload README.md with huggingface_hub

danielhanchen

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96ee8bb
15:48
initial commit

danielhanchen

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Commit History

Jun 15, 2025

Adding `safetensors` variant of this model⁠

Feb 4, 2024

Upload MistralForCausalLM

Upload tokenizer

Upload README.md with huggingface_hub

initial commit