Instructions to use pszemraj/opt-125m-email-generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use pszemraj/opt-125m-email-generation with Transformers:

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

pipe = pipeline("text-generation", model="pszemraj/opt-125m-email-generation")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("pszemraj/opt-125m-email-generation")
model = AutoModelForCausalLM.from_pretrained("pszemraj/opt-125m-email-generation")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use pszemraj/opt-125m-email-generation with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pszemraj/opt-125m-email-generation"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pszemraj/opt-125m-email-generation",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/pszemraj/opt-125m-email-generation

SGLang

How to use pszemraj/opt-125m-email-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 "pszemraj/opt-125m-email-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": "pszemraj/opt-125m-email-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 "pszemraj/opt-125m-email-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": "pszemraj/opt-125m-email-generation",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use pszemraj/opt-125m-email-generation with Docker Model Runner:
```
docker model run hf.co/pszemraj/opt-125m-email-generation
```

NOTE: there is currently a bug with huggingface API for OPT models. Please use the colab notebook to test :)

opt for email generation - 125m

Why write the rest of your email when you can generate it?

from transformers import pipeline
model_tag = "pszemraj/opt-125m-email-generation"
generator = pipeline(
              'text-generation', 
              model=model_tag, 
              use_fast=False,
              do_sample=False,
            )
            
prompt = """
Hello, 
Following up on the bubblegum shipment."""
generator(
    prompt,
    max_length=96,
) # generate

colab notebook for testing/use

About

This model is a fine-tuned version of facebook/opt-125m on an aeslc dataset.

Emails, phone numbers, etc., were attempted to be excluded in a dataset preparation step using clean-text in Python.
Note that API is restricted to generating 64 tokens - you can generate longer emails by using this in a text-generation pipeline object

It achieves the following results on the evaluation set:

Loss: 2.5552

Intended uses & limitations

OPT models cannot be used commercially
here is a GitHub gist for a script to generate emails in the console or to a text file.

Training and evaluation data

the email_body field of train + validation (get more data) from the aeslc dataset.

Training results

Training Loss	Epoch	Step	Validation Loss
2.8245	1.0	129	2.8030
2.521	2.0	258	2.6343
2.2074	3.0	387	2.5595
2.0145	4.0	516	2.5552

Framework versions

Transformers 4.20.1
Pytorch 1.11.0+cu113
Tokenizers 0.12.1

Downloads last month: 1,727

Safetensors

Model size

0.1B params

Tensor type

F32

Model tree for pszemraj/opt-125m-email-generation

Base model

facebook/opt-125m

Finetuned

(116)

this model

pszemraj
/

opt-125m-email-generation