Text Generation
Transformers
PyTorch
Safetensors
English
gpt2
email-generation
text-generation-inference
Instructions to use sagorsarker/emailgenerator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagorsarker/emailgenerator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="sagorsarker/emailgenerator")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("sagorsarker/emailgenerator") model = AutoModelForCausalLM.from_pretrained("sagorsarker/emailgenerator") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use sagorsarker/emailgenerator with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sagorsarker/emailgenerator" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sagorsarker/emailgenerator", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sagorsarker/emailgenerator
- SGLang
How to use sagorsarker/emailgenerator 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 "sagorsarker/emailgenerator" \ --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": "sagorsarker/emailgenerator", "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 "sagorsarker/emailgenerator" \ --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": "sagorsarker/emailgenerator", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use sagorsarker/emailgenerator with Docker Model Runner:
docker model run hf.co/sagorsarker/emailgenerator
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2dd275e | 1 2 3 4 5 6 7 8 9 10 11 12 | ---
language: en
tags:
- email-generation
license: mit
---
EmailGenerator is a gpt-2 fine-tuned text-generation pre-trained model trained on [emailblog](https://www.kaggle.com/datasets/mikeschmidtavemac/emailblog) datasets for [EmailWriter](https://github.com/sagorbrur/EmailWriter) repositories.
For details about this model check [EmailWriter](https://github.com/sagorbrur/EmailWriter) repository.
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