Instructions to use ktrapeznikov/gpt2-medium-topic-small-set with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ktrapeznikov/gpt2-medium-topic-small-set with Transformers:

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

pipe = pipeline("text-generation", model="ktrapeznikov/gpt2-medium-topic-small-set")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ktrapeznikov/gpt2-medium-topic-small-set")
model = AutoModelForCausalLM.from_pretrained("ktrapeznikov/gpt2-medium-topic-small-set")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ktrapeznikov/gpt2-medium-topic-small-set with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ktrapeznikov/gpt2-medium-topic-small-set"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ktrapeznikov/gpt2-medium-topic-small-set",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ktrapeznikov/gpt2-medium-topic-small-set

SGLang

How to use ktrapeznikov/gpt2-medium-topic-small-set 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 "ktrapeznikov/gpt2-medium-topic-small-set" \
    --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": "ktrapeznikov/gpt2-medium-topic-small-set",
		"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 "ktrapeznikov/gpt2-medium-topic-small-set" \
        --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": "ktrapeznikov/gpt2-medium-topic-small-set",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ktrapeznikov/gpt2-medium-topic-small-set with Docker Model Runner:
```
docker model run hf.co/ktrapeznikov/gpt2-medium-topic-small-set
```

gpt2-medium-topic-small-set

Commit History

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Commit History

upload flax model 9901a86

allow flax 3e3d087

Update README.md 69636e2

Update README.md 4cc89d7

Update config.json aea9305

Update README.md 98007e6

Create README.md d048b57

Update from ktrapeznikov 8cd96ce

initial commit 5e57e19

upload flax model

9901a86

allow flax

3e3d087

Update README.md

69636e2

Update README.md

4cc89d7

Update config.json

aea9305

Update README.md

98007e6

Create README.md

d048b57

Update from ktrapeznikov

8cd96ce

initial commit

5e57e19