Instructions to use anezatra/gpt2-alpaca-355M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use anezatra/gpt2-alpaca-355M with Transformers:

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

pipe = pipeline("text-generation", model="anezatra/gpt2-alpaca-355M")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("anezatra/gpt2-alpaca-355M")
model = AutoModelForCausalLM.from_pretrained("anezatra/gpt2-alpaca-355M")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use anezatra/gpt2-alpaca-355M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "anezatra/gpt2-alpaca-355M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "anezatra/gpt2-alpaca-355M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/anezatra/gpt2-alpaca-355M

SGLang

How to use anezatra/gpt2-alpaca-355M 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 "anezatra/gpt2-alpaca-355M" \
    --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": "anezatra/gpt2-alpaca-355M",
		"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 "anezatra/gpt2-alpaca-355M" \
        --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": "anezatra/gpt2-alpaca-355M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use anezatra/gpt2-alpaca-355M with Docker Model Runner:
```
docker model run hf.co/anezatra/gpt2-alpaca-355M
```

OpenAI GPT-2 355M

Model description

This custom GPT-2 model is derived from the gpt2-medium model and trained on the Alpaca dataset. Anezatra team meticulously trained this model on the Alpaca dataset for natural language processing tasks. The model excels in text generation and language understanding tasks, making it ideal for chat applications.

Training Procedure

This model was trained with 4 x A100 GPUs

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 128
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.15
num_epochs: 1

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anezatra
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gpt2-alpaca-355M

OpenAI GPT-2 355M

Model description

Training Procedure

Training hyperparameters

Dataset used to train anezatra/gpt2-alpaca-355M