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mpasila/gpt3-finnish-8B-gptq-4bit
gpt3-finnish-8B-gptq-4bit is a text generation model from mpasila. 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.
GPTQ quantization of TurkuNLP/gpt3-finnish-8B.
Downloads · 30 days
121
52% of all-time downloads
All-time downloads
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4.4 GB on disk
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.safetensors4.4 GB · 100%
How the weights are stored.
I326.4B · 92%
From the Hugging Face model README
GPTQ quantization of TurkuNLP/gpt3-finnish-8B.
Using the following settings:
quantization_config = GPTQConfig(
bits=4,
group_size=128,
dataset="wikitext2",
desc_act=False,
)
Generative Pretrained Transformer with 8B parameteres for Finnish.
TurkuNLP Finnish GPT-3-models are a model family of pretrained monolingual GPT-style language models that are based on BLOOM-architecture. Note that the models are pure language models, meaning that they are not instruction finetuned for dialogue or answering questions.
These models are intended to be used as foundational models that can be e.g. instruction finetuned to serve as modern chat-models.
All models are trained for 300B tokens.
Parameters
| Model | Layers | Dim | Heads | Params |
|---|---|---|---|---|
| Small | 12 | 768 | 12 | 186M |
| Medium | 24 | 1024 | 16 | 437M |
| Large | 24 | 1536 | 16 | 881M |
| XL | 24 | 2064 | 24 | 1.5B |
| ”3B” | 32 | 2560 | 32 | 2.8B |
| ”8B” | 32 | 4096 | 32 | 7.5B |
| "13B" | 40 | 5120 | 40 | 13.3B |
Datasets
We used a combination of multiple Finnish resources.
Sampling ratios
| Dataset | Chars | Ratio | Weight | W.Ratio |
|---|---|---|---|---|
| Parsebank | 35.0B | 16.9% | 1.5 | 22.7% |
| mC4-Fi | 46.3B | 22.4% | 1.0 | 20.0% |
| CC-Fi | 79.6B | 38.5% | 1.0 | 34.4% |
| Fiwiki | 0.8B | 0.4% | 3.0 | 1.0% |
| Lönnrot | 0.8B | 0.4% | 3.0 | 1.0% |
| Yle | 1.6B | 0.8% | 2.0 | 1.4% |
| STT | 2.2B | 1.1% | 2.0 | 1.9% |
| ePub | 13.5B | 6.5% | 1.0 | 5.8% |
| Lehdet | 5.8B | 2.8% | 1.0 | 2.5% |
| Suomi24 | 20.6B | 9.9% | 1.0 | 8.9% |
| Reddit-Fi | 0.7B | 0.4% | 1.0 | 0.3% |
| TOTAL | 207.0B | 100.0% | N/A | 100.0% |
More documentation and a paper coming soon.