occiglot
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occiglot-7b-de-en

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 ---
+license: apache-2.0
+language:
+- en
+- de
+pipeline_tag: text-generation
 ---
+![image/png](https://huggingface.co/datasets/malteos/images/resolve/main/occiglot.medium.png)
+# Occiglot-7B-EU5
+> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
+>
+**Occiglot-7B-DE-EN** is a generative language model with 7B parameters for Germnan and English and trained by the [Occiglot Research Collective](https://ociglot.eu).
+It is based on [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) and trained on 114B tokens of additional multilingual and code data with a block size of 8,192 tokens per sample.
+Note that the model is a general-purpose base model and was not instruction-fine-tuned nor optimized for chat or other applications. We make an instruction tuned variant available as [occiglot-7b-de-en-instruct](https://huggingface.co/occiglot/occiglot-7b-de-en-instruct)
+This is the first release of an ongoing open research project for multilingual language models.
+If you want to train a model for your own language or are working on evaluations, please contact us or join our [Discord server](https://discord.gg/wUpvYs4XvM). **We are open for collaborations!**
+### Model details
+- **Continued-pretraining from:** [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+- **Model type:** Causal decoder-only transformer language model
+- **Languages:** English, German, and code.
+- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
+- **Compute resources:** [HessianAI's 42](https://hessian.ai/)
+- **Contributors:** Manuel Brack, Patrick Schramowski, Pedro Ortiz, Malte Ostendorff, Fabio Barth, Georg Rehm, Kristian Kersting
+- **Research labs:** [Occiglot](https://ociglot.eu) with support from [SAINT](https://www.dfki.de/en/web/research/research-departments/foundations-of-systems-ai) and [SLT](https://www.dfki.de/en/web/research/research-departments/speech-and-language-technology)
+- **Contact:** [Discord](https://discord.gg/wUpvYs4XvM) [hello@occiglot.org](mailto:hello@occiglot.org)
+### How to use
+You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, we
+set a seed for reproducibility:
+```python
+>>> from transformers import pipeline, set_seed
+>>> generator = pipeline('text-generation', model='occiglot/occiglot-7b-eu5')
+>>> set_seed(42)
+>>> generator("Hallo, Ich bin ein Sprachmodell,", max_length=40, num_return_sequences=1)
+[{'generated_text': 'Hallo, Ich bin ein Sprachmodell, das dir bei der Übersetzung von Texten zwischen Deutsch und Englisch helfen kann. Wenn du mir einen Text in Deutsch'}]
+```
+## Dataset
+The training data is the respective subset of the data used for [occiglot-7b-eu5](https://huggingface.co/occiglot/occiglot-7b-eu5), i.e. German plus English and Code.
+The data distribution by language (estimated) is as follows:
+- English: ~34%
+- Code: ~13%
+- German: ~52%
+The training data was prepared using [lm-datasets](https://github.com/malteos/lm-datasets).
+The exact data configuration is [here](https://huggingface.co/occiglot/occiglot-7b-eu5/blob/main/lm-datasets-config.yml).
+## Training settings
+- Continual pre-training on 128 x A100-80GB on [HessianAI's 42](https://hessian.ai/).
+- Framework: [Determined](https://www.determined.ai/)
+- Precision: bf16
+- Optimizer: AdamW (lr: 0.00001, warmup_steps: 420)
+- Global batch size: 512 (with 8192 blocksize) split over 128 GPUs
+- Cosine Annealing with Warmup
+## Tokenizer
+Tokenizer is unchanged from [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
 ## Evaluation
+Preliminary evaluation results can be found below.
+Please note that the non-English results are based on partially machine-translated datasets and English prompts ([Belebele](https://huggingface.co/datasets/facebook/belebele) and [Okapi framework](https://github.com/nlp-uoregon/Okapi)) and thus should be interpreted with caution, e.g., biased towards English model performance.
+Currently, we are working on more suitable benchmarks for Spanish, French, German, and Italian.
+<details>
+<summary>Evaluation results</summary>
+</details>
+## Acknowledgements
+The model training was supported by a compute grant at the [42 supercomputer](https://hessian.ai/)  which is a central component in the development of [hessian AI](https://hessian.ai/), the [AI Innovation Lab](https://hessian.ai/infrastructure/ai-innovationlab/) (funded by the [Hessian Ministry of Higher Education, Research and the Art (HMWK)](https://wissenschaft.hessen.de) & the [Hessian Ministry of the Interior, for Security and Homeland Security (HMinD)](https://innen.hessen.de)) and the [AI Service Centers](https://hessian.ai/infrastructure/ai-service-centre/) (funded by the [German Federal Ministry for Economic Affairs and Climate Action (BMWK)](https://www.bmwk.de/Navigation/EN/Home/home.html)).
+The curation of the training data is partially funded by the [German Federal Ministry for Economic Affairs and Climate Action (BMWK)](https://www.bmwk.de/Navigation/EN/Home/home.html)
+through the project [OpenGPT-X](https://opengpt-x.de/en/) (project no. 68GX21007D).
+## License
+[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
+## See also
+- https://huggingface.co/collections/occiglot/occiglot-eu5-7b-v01-65dbed502a6348b052695e01