Instructions to use FrostAura/gpt-neo-1.3B-fiction-novel-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FrostAura/gpt-neo-1.3B-fiction-novel-generation with Transformers:

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

pipe = pipeline("text-generation", model="FrostAura/gpt-neo-1.3B-fiction-novel-generation")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("FrostAura/gpt-neo-1.3B-fiction-novel-generation")
model = AutoModelForMultimodalLM.from_pretrained("FrostAura/gpt-neo-1.3B-fiction-novel-generation")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FrostAura/gpt-neo-1.3B-fiction-novel-generation with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FrostAura/gpt-neo-1.3B-fiction-novel-generation"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FrostAura/gpt-neo-1.3B-fiction-novel-generation",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FrostAura/gpt-neo-1.3B-fiction-novel-generation

SGLang

How to use FrostAura/gpt-neo-1.3B-fiction-novel-generation 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 "FrostAura/gpt-neo-1.3B-fiction-novel-generation" \
    --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": "FrostAura/gpt-neo-1.3B-fiction-novel-generation",
		"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 "FrostAura/gpt-neo-1.3B-fiction-novel-generation" \
        --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": "FrostAura/gpt-neo-1.3B-fiction-novel-generation",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FrostAura/gpt-neo-1.3B-fiction-novel-generation with Docker Model Runner:
```
docker model run hf.co/FrostAura/gpt-neo-1.3B-fiction-novel-generation
```

fa.intelligence.models.generative.novels.fiction

Description

This FrostAura Intelligence model is a fine-tuned version of EleutherAI/gpt-neo-1.3B for fictional text content generation.

Getting Started

PIP Installation

pip install -U --no-cache-dir transformers

Usage

from transformers import pipeline

model_name: str = 'FrostAura/gpt-neo-1.3B-fiction-novel-generation'
generator: pipeline = pipeline('text-generation', model=model_name)

prompt: str = 'So far my day has been '
gen_text: str = generator(prompt, do_sample=True, min_length=50)

print(f'Result: {gen_text}')

Further Fine-Tuning

in development

Support

If you enjoy FrostAura open-source content and would like to support us in continuous delivery, please consider a donation via a platform of your choice.

Supported Platforms	Link
PayPal	Donate via Paypal

For any queries, contact dean.martin@frostaura.net.

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