postbot/emailgen-pythia-410m-deduped
By postbot · ↓ 5 · ♥ 0 · Updated 2023-12-20
What's in this repo
This page lists the files in postbot/emailgen-pythia-410m-deduped, including model.onnx.
- 1 ONNX models (.onnx files)
- 14 files, including 8 .json, 1 .md, 1 .onnx, 1 .safetensors, 1 .bin
- Last updated 2023-12-20
ONNX files
| File | Size | Download |
|---|---|---|
| model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
emailgen-pythia-410m-deduped
This model is a fine-tuned version of EleutherAI/pythia-410m-deduped on email data. It achieves the following results on the evaluation set:
- Loss: 2.1018
- Accuracy: 0.6157
- perplexity: 8.181
Model description
- fine-tuned on dataset of emails for 4 epochs
- intended use: "text completion" of partially written emails
Usage example
from transformers import pipeline
model_tag = "postbot/emailgen-pythia-410m-deduped"
generator = pipeline(
"text-generation",
model=model_tag,
)
prompt = """
Hello,
Following up on the bubblegum shipment."""
result = generator(
prompt,
) # generate
print(result[0]["generated_text"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 26.65 |
| ARC (25-shot) | 27.9 |
| HellaSwag (10-shot) | 40.04 |
| MMLU (5-shot) | 27.35 |
| TruthfulQA (0-shot) | 38.2 |
| Winogrande (5-shot) | 52.09 |
| GSM8K (5-shot) | 0.0 |
| DROP (3-shot) | 0.99 |
Model info
text-generation
transformers
transformers
pytorch
onnx
safetensors
gpt_neox
text-generation
generated_from_trainer
en
dataset:postbot/multi-emails-hq
base_model:EleutherAI/pythia-410m-deduped
base_model:quantized:EleutherAI/pythia-410m-deduped
license:apache-2.0
↓ 5
♥ 0
Created: 2023-02-15
Updated: 2023-12-20
View on Hugging FaceFiles (14)
.gitattributes
.gitignore
README.md
all_results.json
config.json
eval_results.json
generation_config.json
model.onnx
ONNX
model.safetensors
pytorch_model.bin
special_tokens_map.json
tokenizer.json
tokenizer_config.json
train_results.json