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
- 31
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for pszemraj/opt-125m-email-generation
Base model
facebook/opt-125m