Instructions to use nlplab/PhishingEmailGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nlplab/PhishingEmailGeneration with Transformers:

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

pipe = pipeline("text-generation", model="nlplab/PhishingEmailGeneration")

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

tokenizer = AutoTokenizer.from_pretrained("nlplab/PhishingEmailGeneration")
model = AutoModelForCausalLM.from_pretrained("nlplab/PhishingEmailGeneration", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nlplab/PhishingEmailGeneration with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/nlplab/PhishingEmailGeneration

SGLang

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

Docker Model Runner
How to use nlplab/PhishingEmailGeneration with Docker Model Runner:
```
docker model run hf.co/nlplab/PhishingEmailGeneration
```

PhishingEmailGeneration

Commit History

Apr 17, 2023

15:15
Adding `safetensors` variant of this model⁠

SFconvertbot

01ec9f8

Mar 18, 2022

08:17
0318 new model

GiGi

b51c295

Jan 21, 2022

06:28
new model gpt-2-medium

GiGi

af35b32
06:07
Create .gitattributes

Yen-Hsiang Wang

bf9d050
06:06
Delete .gitattributes

Yen-Hsiang Wang

077c62f

Dec 7, 2021

15:16
🛠 fix: Add special token

Tomy Hsieh

Unverified signature
016776f
14:38
Upload artifact

Tomy Hsieh

Unverified signature
b8c68d0
14:35
initial commit

system HF Staff

dad4bbd

Commit History

Apr 17, 2023

Adding `safetensors` variant of this model⁠

Mar 18, 2022

0318 new model

Jan 21, 2022

new model gpt-2-medium

Create .gitattributes

Delete .gitattributes

Dec 7, 2021

🛠 fix: Add special token

Upload artifact

initial commit