Instructions to use Isotonic/gpt2-context_generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Isotonic/gpt2-context_generator with Transformers:

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

pipe = pipeline("text-generation", model="Isotonic/gpt2-context_generator")

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

tokenizer = AutoTokenizer.from_pretrained("Isotonic/gpt2-context_generator")
model = AutoModelForCausalLM.from_pretrained("Isotonic/gpt2-context_generator", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Isotonic/gpt2-context_generator with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Isotonic/gpt2-context_generator

SGLang

How to use Isotonic/gpt2-context_generator 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 "Isotonic/gpt2-context_generator" \
    --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": "Isotonic/gpt2-context_generator",
		"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 "Isotonic/gpt2-context_generator" \
        --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": "Isotonic/gpt2-context_generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Isotonic/gpt2-context_generator with Docker Model Runner:
```
docker model run hf.co/Isotonic/gpt2-context_generator
```

gpt2-context_generator

Commit History

Sep 11, 2023

14:28
Librarian Bot: Add base_model information to model⁠

librarian-bot

a2b7350

Sep 6, 2023

18:11
Update README.md

Isotonic

88ac4d8

Aug 28, 2023

12:34
Adding `safetensors` variant of this model (#1)⁠

Isotonic +1: SFconvertbot

fbb8ffb
12:33
gpt2 Tokenizer files

Isotonic

9795c06
12:27
Update config.json

Isotonic

3a036da
05:50
Update README.md

Isotonic

bc8ae33
05:48
Update config.json

Isotonic

daa0405
05:45
Update README.md

Isotonic

ea44731
05:39
update model card README.md

Isotonic

3a898ce
05:36
End of training

Isotonic

7be2954
05:33
initial commit

Isotonic

0b8ff91

Commit History

Sep 11, 2023

Librarian Bot: Add base_model information to model⁠

Sep 6, 2023

Update README.md

Aug 28, 2023

Adding `safetensors` variant of this model (#1)⁠

gpt2 Tokenizer files

Update config.json

Update README.md

Update config.json

Update README.md

update model card README.md

End of training

initial commit