Text Generation
Transformers
ONNX
Safetensors
Transformers.js
English
gpt2
news
text-generation-inference
Instructions to use kulia-moon/News2GPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kulia-moon/News2GPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="kulia-moon/News2GPT")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("kulia-moon/News2GPT") model = AutoModelForCausalLM.from_pretrained("kulia-moon/News2GPT", device_map="auto") - Transformers.js
How to use kulia-moon/News2GPT with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'kulia-moon/News2GPT'); - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use kulia-moon/News2GPT with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "kulia-moon/News2GPT" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "kulia-moon/News2GPT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/kulia-moon/News2GPT
- SGLang
How to use kulia-moon/News2GPT 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 "kulia-moon/News2GPT" \ --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": "kulia-moon/News2GPT", "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 "kulia-moon/News2GPT" \ --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": "kulia-moon/News2GPT", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use kulia-moon/News2GPT with Docker Model Runner:
docker model run hf.co/kulia-moon/News2GPT
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Download README.md from kulia-moon/News2GPT: direct link, hf CLI and curl.
- Browser
- Download file 256 Bytes
-
https://huggingface.co/kulia-moon/News2GPT/resolve/main/README.md
- Command line
-
hf download hf://kulia-moon/News2GPT/README.md
-
curl -L -o README.md https://huggingface.co/kulia-moon/News2GPT/resolve/main/README.md
256 Bytes
metadata
license: mit
datasets:
- abisee/cnn_dailymail
- SetFit/ag_news
- Yelp/yelp_review_full
- rajpurkar/squad
language:
- en
base_model:
- distilbert/distilgpt2
library_name: transformers
tags:
- news
- transformers.js