Instructions to use KefanSong/checkpoint-2500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use KefanSong/checkpoint-2500 with Transformers:

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

pipe = pipeline("text-generation", model="KefanSong/checkpoint-2500")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("KefanSong/checkpoint-2500")
model = AutoModelForCausalLM.from_pretrained("KefanSong/checkpoint-2500", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use KefanSong/checkpoint-2500 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KefanSong/checkpoint-2500"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "KefanSong/checkpoint-2500",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/KefanSong/checkpoint-2500

SGLang

How to use KefanSong/checkpoint-2500 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 "KefanSong/checkpoint-2500" \
    --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": "KefanSong/checkpoint-2500",
		"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 "KefanSong/checkpoint-2500" \
        --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": "KefanSong/checkpoint-2500",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use KefanSong/checkpoint-2500 with Docker Model Runner:
```
docker model run hf.co/KefanSong/checkpoint-2500
```

checkpoint-2500

Commit History

Upload config

ccdb684
verified

Gary Song commited on Aug 31, 2024

Upload tokenizer

77f7dc7
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Gary Song commited on Aug 31, 2024

Upload model

987abef
verified

Gary Song commited on Aug 31, 2024

initial commit

75b5026
verified

Gary Song commited on Aug 30, 2024

Commit History

Upload config ccdb684 verified

Upload tokenizer 77f7dc7 verified

Upload model 987abef verified

initial commit 75b5026 verified

Upload config

ccdb684
verified

Upload tokenizer

77f7dc7
verified

Upload model

987abef
verified

initial commit

75b5026
verified