---
license: apache-2.0
language:
- en
library_name: transformers
datasets:
- budecosystem/intellecta
---
Democratizing access to LLMs for the open-source community.
Let's advance AI, together.
----
## Introduction 🎉
We are thrilled to announce the open-sourcing of our boomer-634m model, an important milestone in our ongoing AI research. This model, with 634 million parameters, was meticulously pre-trained from scratch on a custom synthetic dataset comprising 12 billion tokens.
## Run the model
Here is a quick guide to get you started with boomer-634m:
Please note that, at the moment, `trust_remote_code=True` is required for running the model.
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("budecosystem/boomer-634m",
trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("budecosystem/boomer-634m")
input_ids = tokenizer("Explain why the sky is blue.", return_tensors='pt').to(model.device)["input_ids"]
outputs = model.generate(input_ids, max_new_tokens=216)
print(tokenizer.batch_decode(outputs))
```
## Evaluations
The boomer-634m model has been rigorously evaluated on various benchmarks, showcasing its robust performance across different tasks:
| Model Name | MMLU | ARC | Hellaswag | GSM8K | Winogrande | MathQA | logiqa |
|--------------|-------|-------|-----------|-------|------------|--------|--------|
| boomer-634m | 25.91 | 29.86 | 39.24 | 1.67 | 50.67 | 23.55 | 28.42 |
### Final thought on Boomer!
Embarking on the journey with boomer-634m is just the beginning. We are committed to developing more advanced, efficient, and accessible AI models. Join us in this exciting adventure to shape the future of AI.
### Aknowledgements
Our heartfelt thanks go to the open-source community and the trailblazers in AI research whose work has paved the way for innovations like boomer-634m.