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budecosystem/boomer-634m
boomer-634m is a text generation model from budecosystem. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
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Downloads · 30 days
305
20% of all-time downloads
All-time downloads
1.5K
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634M
1.3 GB on disk
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.safetensors1.3 GB · 100%
From the Hugging Face model README
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.
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.
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))
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 |
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.
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.