Create README.md

README.md

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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-DE-EN-Instruct
+
+> 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-Instruct** is a the instruct version of [occiglot-7b-eu5](https://huggingface.co/occiglot/occiglot-7b-eu5/), a generative language model with 7B parameters supporting German and English and trained by the [Occiglot Research Collective](https://occiglot.github.io/occiglot/).
+It was trained on 180M tokens of additional multilingual and code instructions.
+Note that the model was not safety aligned and might generate problematic outputs.
+
+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!**
+
+*Special thanks go to **[Disco Research](https://huggingface.co/DiscoResearch)**, **[Jan Philipp Harries](https://huggingface.co/jphme)**, and **[Björn Plüster](https://huggingface.co/bjoernp)** for sharing the German dataset with us*
+
+### Model details
+
+- **Instruction tuned from:** [occiglot-7b-de-en](https://huggingface.co/occiglot/occiglot-7b-de-en)
+- **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:** [DFKI cluster](https://www.dfki.de/en/web)
+- **Contributors:** Manuel Brack, Patrick Schramowski, Pedro Ortiz, Malte Ostendorff, Fabio Barth, Georg Rehm, Kristian Kersting
+- **Research labs:** [Occiglot](https://occiglot.github.io/occiglot/) 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) 
+
+### How to use
+
+The model was trained using the chatml instruction template. You can use the transformers chat template feature for interaction.
+Since the generation relies on some randomness, we
+set a seed for reproducibility:
+
+```python
+>>> from transformers import AutoTokenizer, MistralForCausalLM, set_seed
+>>> tokenizer = AutoTokenizer.from_pretrained("occiglot/occiglot-7b-de-en-instruct")
+>>> model = MistralForCausalLM.from_pretrained('occiglot/occiglot-7b-de-en-instruct')  # You may want to use bfloat16 and/or move to GPU here
+>>> set_seed(42)
+>>> messages = [
+>>>    {"role": "system", 'content': 'You are a helpful assistant. Please give short and concise answers.'},
+>>>    {"role": "user", "content": "Wer ist der deutsche Bundeskanzler?"},
+>>> ]
+>>> tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_dict=False, return_tensors='pt',)
+>>> set_seed(42)
+>>> outputs = model.generate(tokenized_chat.to('cuda'), max_new_tokens=200,)
+>>> tokenizer.decode(out[0][len(tokenized_chat[0]):])
+'Der deutsche Bundeskanzler ist Olaf Scholz.'
+```
+
+## Dataset
+
+The training data was split evenly between German and English based on the total number of tokens. We would like to thank [Disco Research](https://huggingface.co/DiscoResearch), [Jan Philipp Harries](https://huggingface.co/jphme), and [Björn Plüster](https://huggingface.co/bjoernp) for making their dataset available to us. 
+
+**English and Code**
+ - [Open-Hermes-2B](https://huggingface.co/datasets/teknium/OpenHermes-2.5)
+
+**German**
+ - [DiscoLM German Dataset](https://huggingface.co/DiscoResearch) includes the publicly available [germanrag](https://huggingface.co/datasets/DiscoResearch/germanrag) dataset
+ - [OASST-2](https://huggingface.co/datasets/OpenAssistant/oasst2) (German subset)
+ - [Aya-Dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) (German subset)
+
+
+## Training settings
+
+- Full instruction fine-tuning on 8xH100.
+- 0.6 - 4 training epochs (depending on dataset sampling).
+- Framework: [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
+- Precision: bf16
+- Optimizer: AdamW
+- Global batch size: 128 (with 8192 context length)
+- 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>
+
+### All 5 Languages
+
+|                            |      avg |   arc_challenge |   belebele |   hellaswag |     mmlu |   truthfulqa |
+|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
+| Occiglot-7b-eu5            | 0.516895 |        0.508109 |   0.675556 |    0.718963 | 0.402064 |     0.279782 |
+| Occiglot-7b-eu5-instruct   | 0.537799 |        0.53632  |   0.691111 |    0.731918 | 0.405198 |     0.32445  |
+| Occiglot-7b-de-en          | 0.518337 |        0.496297 |   0.715111 |    0.669034 | 0.412545 |     0.298697 |
+| Occiglot-7b-de-en-instruct | 0.543173 |        0.530826 |   0.745778 |    0.67676  | 0.411326 |     0.351176 |
+| Leo-mistral-hessianai-7b   | 0.484806 |        0.462103 |   0.653556 |    0.642242 | 0.379208 |     0.28692  |
+| Mistral-7b-v0.1            | 0.547111 |        0.528937 |   0.768444 |    0.682516 | 0.448253 |     0.307403 |
+| Mistral-7b-instruct-v0.2   | 0.56713  |        0.547228 |   0.741111 |    0.69455  | 0.422501 |     0.430262 |
+
+
+### English
+
+|                            |      avg |   arc_challenge |   belebele |   hellaswag |     mmlu |   truthfulqa |
+|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
+| Occiglot-7b-eu5            | 0.59657  |        0.530717 |   0.726667 |    0.789882 | 0.531904 |     0.403678 |
+| Occiglot-7b-eu5-instruct   | 0.617905 |        0.558874 |   0.746667 |    0.799841 | 0.535109 |     0.449    |
+| Occiglot-7b-de-en          | 0.518337 |        0.496297 |   0.715111 |    0.669034 | 0.412545 |     0.298697 |
+| Occiglot-7b-de-en-instruct | 0.543173 |        0.530826 |   0.745778 |    0.67676  | 0.411326 |     0.351176 |
+| Leo-mistral-hessianai-7b   | 0.600949 |        0.522184 |   0.736667 |    0.777833 | 0.538812 |     0.429248 |
+| Mistral-7b-v0.1            | 0.668385 |        0.612628 |   0.844444 |    0.834097 | 0.624555 |     0.426201 |
+| Mistral-7b-instruct-v0.2   | 0.713657 |        0.637372 |   0.824444 |    0.846345 | 0.59201  |     0.668116 |
+
+### German
+
+|                            |      avg |   arc_challenge_de |   belebele_de |   hellaswag_de |   mmlu_de |   truthfulqa_de |
+|:---------------------------|---------:|-------------------:|--------------:|---------------:|----------:|----------------:|
+| Occiglot-7b-eu5            | 0.508311 |           0.493584 |      0.646667 |       0.666631 |  0.483406 |        0.251269 |
+| Occiglot-7b-eu5-instruct   | 0.531506 |           0.529512 |      0.667778 |       0.685205 |  0.488234 |        0.286802 |
+| Occiglot-7b-de-en          | 0.540085 |           0.50556  |      0.743333 |       0.67421  |  0.514633 |        0.26269  |
+| Occiglot-7b-de-en-instruct | 0.566474 |           0.54491  |      0.772222 |       0.688407 |  0.515915 |        0.310914 |
+| Leo-mistral-hessianai-7b   | 0.517766 |           0.474765 |      0.691111 |       0.682109 |  0.488309 |        0.252538 |
+| Mistral-7b-v0.1            | 0.527957 |           0.476476 |      0.738889 |       0.610589 |  0.529567 |        0.284264 |
+| Mistral-7b-instruct-v0.2   | 0.535215 |           0.485885 |      0.688889 |       0.622438 |  0.501961 |        0.376904 |
+
+</details>
+
+## Acknowledgements
+
+The pre-trained 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
+- https://huggingface.co/NikolayKozloff/occiglot-7b-de-en-GGUF