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## Model Details
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### Model Description
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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<!-- Provide the basic links for the model. -->
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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### Direct Use
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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---
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language:
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- fi
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pipeline_tag: text-generation
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license: apache-2.0
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GPTQ conversion of [TurkuNLP/gpt3-finnish-8B](https://huggingface.co/TurkuNLP/gpt3-finnish-8B/).
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Using the following settings:
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```
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quantization_config = GPTQConfig(
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bits=4,
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group_size=128,
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dataset="wikitext2",
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desc_act=False,
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)
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```
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# Original Model card:
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Generative Pretrained Transformer with 8B parameteres for Finnish.
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TurkuNLP Finnish GPT-3-models are a model family of pretrained monolingual GPT-style language models that are based on BLOOM-architecture.
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Note that the models are pure language models, meaning that they are not [instruction finetuned](https://arxiv.org/abs/2203.02155) for dialogue
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or answering questions.
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These models are intended to be used as foundational models that can be e.g. instruction finetuned to serve as modern chat-models.
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All models are trained for 300B tokens.
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**Parameters**
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| Model | Layers | Dim | Heads | Params |
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|--------|--------|------|-------|--------|
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| Small | 12 | 768 | 12 | 186M |
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| Medium | 24 | 1024 | 16 | 437M |
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| Large | 24 | 1536 | 16 | 881M |
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| XL | 24 | 2064 | 24 | 1.5B |
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| ”3B” | 32 | 2560 | 32 | 2.8B |
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| ”8B” | 32 | 4096 | 32 | 7.5B |
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| "13B" | 40 | 5120 | 40 | 13.3B |
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**Datasets**
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We used a combination of multiple Finnish resources.
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* Finnish Internet Parsebank https://turkunlp.org/finnish_nlp.html
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mC4 multilingual colossal, cleaned Common Crawl https://huggingface.co/datasets/mc4
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* Common Crawl Finnish https://TODO
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* Finnish Wikipedia https://fi.wikipedia.org/wiki
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* Lönnrot Projekti Lönnrot http://www.lonnrot.net/
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* ePub National library ”epub” collection
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* National library ”lehdet” collection
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* Suomi24 The Suomi 24 Corpus 2001-2020 http://urn.fi/urn:nbn:fi:lb-2021101527
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* Reddit r/Suomi submissions and comments https://www.reddit.com/r/Suomi
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* STT Finnish News Agency Archive 1992-2018 http://urn.fi/urn:nbn:fi:lb-2019041501
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* Yle Finnish News Archive 2011-2018 http://urn.fi/urn:nbn:fi:lb-2017070501
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* Yle Finnish News Archive 2019-2020 http://urn.fi/urn:nbn:fi:lb-2021050401
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* Yle News Archive Easy-to-read Finnish 2011-2018 http://urn.fi/urn:nbn:fi:lb-2019050901
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* Yle News Archive Easy-to-read Finnish 2019-2020 http://urn.fi/urn:nbn:fi:lb-2021050701
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* ROOTS TODO
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**Sampling ratios**
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|Dataset | Chars | Ratio | Weight | W.Ratio |
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|----------|--------|---------|--------|---------|
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|Parsebank | 35.0B | 16.9\% | 1.5 | 22.7\%|
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|mC4-Fi | 46.3B | 22.4\% | 1.0 | 20.0\%|
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|CC-Fi | 79.6B | 38.5\% | 1.0 | 34.4\%|
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|Fiwiki | 0.8B | 0.4\% | 3.0 | 1.0\%|
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|Lönnrot | 0.8B | 0.4\% | 3.0 | 1.0\%|
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|Yle | 1.6B | 0.8\% | 2.0 | 1.4\%|
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|STT | 2.2B | 1.1\% | 2.0 | 1.9\%|
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|ePub | 13.5B | 6.5\% | 1.0 | 5.8\%|
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|Lehdet | 5.8B | 2.8\% | 1.0 | 2.5\%|
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|Suomi24 | 20.6B | 9.9\% | 1.0 | 8.9\%|
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|Reddit-Fi | 0.7B | 0.4\% | 1.0 | 0.3\%|
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|**TOTAL** | **207.0B** | **100.0\%** | **N/A** | **100.0\%** |
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More documentation and a paper coming soon.
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