Instructions to use ClassCat/gpt2-small-basque-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ClassCat/gpt2-small-basque-v2 with Transformers:

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

pipe = pipeline("text-generation", model="ClassCat/gpt2-small-basque-v2")

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

tokenizer = AutoTokenizer.from_pretrained("ClassCat/gpt2-small-basque-v2")
model = AutoModelForCausalLM.from_pretrained("ClassCat/gpt2-small-basque-v2", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ClassCat/gpt2-small-basque-v2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ClassCat/gpt2-small-basque-v2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ClassCat/gpt2-small-basque-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ClassCat/gpt2-small-basque-v2

SGLang

How to use ClassCat/gpt2-small-basque-v2 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 "ClassCat/gpt2-small-basque-v2" \
    --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": "ClassCat/gpt2-small-basque-v2",
		"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 "ClassCat/gpt2-small-basque-v2" \
        --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": "ClassCat/gpt2-small-basque-v2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ClassCat/gpt2-small-basque-v2 with Docker Model Runner:
```
docker model run hf.co/ClassCat/gpt2-small-basque-v2
```

gpt2-small-basque-v2

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Commit History

Jun 28, 2023

Adding `safetensors` variant of this model⁠

Jul 20, 2022

add model

Jul 19, 2022

Update README.md

Jul 18, 2022

add model

Create README.md

add model

add model

add model

Jul 17, 2022

add model

add model

add model

add tokenizer

add model

initial commit