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README.md
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---
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license: apache-2.0
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language:
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- en
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- es
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pipeline_tag: text-generation
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---
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![image/png](https://huggingface.co/datasets/malteos/images/resolve/main/occiglot.medium.png)
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# Occiglot-7B-ES-EN-Instruct
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> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
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>
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**Occiglot-7B-ES-EN-Instruct** is a the instruct version of [occiglot-7b-es-en](https://huggingface.co/occiglot/occiglot-7b-es-en), a generative language model with 7B parameters supporting the Spanish and English and trained by the [Occiglot Research Collective](https://occiglot.github.io/occiglot/).
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It was trained on 160M tokens of additional multilingual and code instructions.
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Note that the model was not safety aligned and might generate problematic outputs.
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This is the first release of an ongoing open research project for multilingual language models.
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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!**
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### Model details
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- **Instruction tuned from:** [occiglot-7b-es-en](https://huggingface.co/occiglot/occiglot-7b-es-en)
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- **Model type:** Causal decoder-only transformer language model
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- **Languages:** English, Spanish, and code.
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- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
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- **Compute resources:** [DFKI cluster](https://www.dfki.de/en/web)
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- **Contributors:** Manuel Brack, Patrick Schramowski, Pedro Ortiz, Malte Ostendorff, Fabio Barth, Georg Rehm, Kristian Kersting
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- **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)
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- **Contact:** [Discord](https://discord.gg/wUpvYs4XvM)
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### How to use
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The model was trained using the chatml instruction template. You can use the transformers chat template feature for interaction.
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Since the generation relies on some randomness, we
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set a seed for reproducibility:
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```python
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>>> from transformers import AutoTokenizer, MistralForCausalLM, set_seed
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>>> tokenizer = AutoTokenizer.from_pretrained("occiglot/occiglot-7b-es-en-instruct")
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>>> model = MistralForCausalLM.from_pretrained('occiglot/occiglot-7b-es-en-instruct') # You may want to use bfloat16 and/or move to GPU here
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>>> set_seed(42)
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>>> messages = [
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>>> {"role": "system", 'content': 'You are a helpful assistant. Please give short and concise answers.'},
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>>> {"role": "user", "content": "¿quién es el presidente del gobierno español?"},
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>>> ]
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>>> tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_dict=False, return_tensors='pt',)
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>>> set_seed(42)
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>>> outputs = model.generate(tokenized_chat.to('cuda'), max_new_tokens=200,)
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>>> tokenizer.decode(out[0][len(tokenized_chat[0]):])
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'Actualmente el presidente del gobierno español es Pedro Sánchez Pérez-Castejón'
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```
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## Dataset
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The training data was split evenly amongst Spanish and English based on the total number of tokens.
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**English and Code**
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- [Open-Hermes-2B](https://huggingface.co/datasets/teknium/OpenHermes-2.5)
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**Spanish**
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- [Mentor-ES](https://huggingface.co/datasets/projecte-aina/MentorES)
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- [Squad-es](https://huggingface.co/datasets/squad_es)
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- [OASST-2](https://huggingface.co/datasets/OpenAssistant/oasst2) (Spanish subset)
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- [Aya-Dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) (Spanish subset)
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## Training settings
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- Full instruction fine-tuning on 8xH100.
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- 0.6 - 4 training epochs (depending on dataset sampling).
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- Framework: [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
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- Precision: bf16
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- Optimizer: AdamW
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- Global batch size: 128 (with 8192 context length)
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- Cosine Annealing with Warmup
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## Tokenizer
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Tokenizer is unchanged from [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
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## Evaluation
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Preliminary evaluation results can be found below.
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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.
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Currently, we are working on more suitable benchmarks for Spanish, French, German, and Italian.
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<details>
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<summary>Evaluation results</summary>
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### All 5 Languages
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| | avg | arc_challenge | belebele | hellaswag | mmlu | truthfulqa |
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|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
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| Occiglot-7b-eu5 | 0.516895 | 0.508109 | 0.675556 | 0.718963 | 0.402064 | 0.279782 |
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| Occiglot-7b-eu5-instruct | 0.537799 | 0.53632 | 0.691111 | 0.731918 | 0.405198 | 0.32445 |
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| Occiglot-7b-es-en | 0.483388 | 0.482949 | 0.606889 | 0.653902 | 0.398922 | 0.274277 |
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| Occiglot-7b-es-en-instruct | 0.504023 | 0.494576 | 0.65 | 0.670847 | 0.406176 | 0.298513 |
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| Lince-mistral-7b-it-es | 0.543427 | 0.540222 | 0.745111 | 0.692931 | 0.426241 | 0.312629 |
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| Mistral-7b-v0.1 | 0.547111 | 0.528937 | 0.768444 | 0.682516 | 0.448253 | 0.307403 |
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| Mistral-7b-instruct-v0.2 | 0.56713 | 0.547228 | 0.741111 | 0.69455 | 0.422501 | 0.430262 |
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### English
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| | avg | arc_challenge | belebele | hellaswag | mmlu | truthfulqa |
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|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
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| Occiglot-7b-eu5 | 0.59657 | 0.530717 | 0.726667 | 0.789882 | 0.531904 | 0.403678 |
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| Occiglot-7b-eu5-instruct | 0.617905 | 0.558874 | 0.746667 | 0.799841 | 0.535109 | 0.449 |
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| Occiglot-7b-es-en | 0.593609 | 0.543515 | 0.697778 | 0.788289 | 0.548355 | 0.390109 |
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| Occiglot-7b-es-en-instruct | 0.615707 | 0.552048 | 0.736667 | 0.797451 | 0.557328 | 0.435042 |
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| Leo-mistral-hessianai-7b | 0.600949 | 0.522184 | 0.736667 | 0.777833 | 0.538812 | 0.429248 |
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| Mistral-7b-v0.1 | 0.668385 | 0.612628 | 0.844444 | 0.834097 | 0.624555 | 0.426201 |
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| Mistral-7b-instruct-v0.2 | 0.713657 | 0.637372 | 0.824444 | 0.846345 | 0.59201 | 0.668116 |
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### Spanish
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| | avg | arc_challenge_es | belebele_es | hellaswag_es | mmlu_es | truthfulqa_es |
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|:---------------------------|---------:|-------------------:|--------------:|---------------:|----------:|----------------:|
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| Occiglot-7b-eu5 | 0.533194 | 0.508547 | 0.676667 | 0.725411 | 0.499325 | 0.25602 |
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| Occiglot-7b-eu5-instruct | 0.548155 | 0.535043 | 0.68 | 0.737039 | 0.503525 | 0.285171 |
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| Occiglot-7b-es-en | 0.527264 | 0.529915 | 0.627778 | 0.72253 | 0.512749 | 0.243346 |
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| Occiglot-7b-es-en-instruct | 0.5396 | 0.545299 | 0.636667 | 0.734372 | 0.524374 | 0.257288 |
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| Lince-mistral-7b-it-es | 0.547212 | 0.52906 | 0.721111 | 0.687967 | 0.512749 | 0.285171 |
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| Mistral-7b-v0.1 | 0.554817 | 0.528205 | 0.747778 | 0.672712 | 0.544023 | 0.281369 |
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| Mistral-7b-instruct-v0.2 | 0.568575 | 0.54188 | 0.73 | 0.685406 | 0.511699 | 0.373891 |
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</details>
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## Acknowledgements
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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)).
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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)
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through the project [OpenGPT-X](https://opengpt-x.de/en/) (project no. 68GX21007D).
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## License
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[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
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## See also
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- https://huggingface.co/collections/occiglot/occiglot-eu5-7b-v01-65dbed502a6348b052695e01
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- https://huggingface.co/NikolayKozloff/occiglot-7b-es-en-GGUF
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