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--- |
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datasets: |
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- LeoLM/OpenSchnabeltier |
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- OpenAssistant/OASST-DE |
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- FreedomIntelligence/alpaca-gpt4-deutsch |
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- FreedomIntelligence/evol-instruct-deutsch |
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- LeoLM/German_Poems |
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- LeoLM/German_Songs |
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language: |
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- en |
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- de |
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library_name: transformers |
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pipeline_tag: text-generation |
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--- |
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# LAION LeoLM: **L**inguistically **E**nhanced **O**pen **L**anguage **M**odel |
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Meet LeoLM, the first open and commercially available German Foundation Language Model built on Llama-2. |
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Our models extend Llama-2's capabilities into German through continued pretraining on a large corpus of German-language and mostly locality specific text. |
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Thanks to a compute grant at HessianAI's new supercomputer **42**, we release two foundation models trained with 8k context length, |
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[`LeoLM/leo-hessianai-7b`](https://huggingface.co/LeoLM/leo-hessianai-7b) and [`LeoLM/leo-hessianai-13b`](https://huggingface.co/LeoLM/leo-hessianai-13b) under the [Llama-2 community license](https://huggingface.co/meta-llama/Llama-2-70b/raw/main/LICENSE.txt) (70b also coming soon! 👀). |
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With this release, we hope to bring a new wave of opportunities to German open-source and commercial LLM research and accelerate adoption. |
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Read our [blog post]() or our paper (preprint coming soon) for more details! |
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*A project by Björn Plüster and Christoph Schuhmann in collaboration with LAION and HessianAI.* |
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## LeoLM Chat |
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`LeoLM/leo-hessianai-7b-chat` is a German chat model built on our foundation model `LeoLM/leo-hessianai-7b` and finetuned on a selection of German instruction datasets. |
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The model performs exceptionally well on writing, explanation and discussion tasks but struggles somewhat with math and advanced reasoning. See our MT-Bench-DE scores: |
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``` |
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``` |
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## Model Details |
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- **Finetuned from:** [LeoLM/leo-hessianai-7b](https://huggingface.co/LeoLM/leo-hessianai-7b) |
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- **Model type:** Causal decoder-only transformer language model |
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- **Language:** English and German |
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- **Demo:** [Continuations for 250 random prompts (TGI, 4bit nf4 quantization)](https://open-assistant.github.io/oasst-model-eval/?f=https%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Foasst-sft%2F2023-08-22_OpenAssistant_llama2-70b-oasst-sft-v10_sampling_noprefix2_nf4.json%0A) |
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- **License:** [LLAMA 2 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/meta-llama/Llama-2-70b/raw/main/LICENSE.txt) |
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- **Contact:** [LAION Discord](https://discord.com/invite/eq3cAMZtCC) or [Björn Plüster](mailto:[email protected]) |
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## Prompting / Prompt Template |
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Prompt dialogue template (ChatML format): |
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``` |
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""" |
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<|im_start|>system |
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{system_message}<|im_end|> |
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<|im_start|>user |
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{prompt}<|im_end|> |
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<|im_start|>assistant |
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""" |
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``` |
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The model input can contain multiple conversation turns between user and assistant, e.g. |
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``` |
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<|im_start|>user |
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{prompt 1}<|im_end|> |
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<|im_start|>assistant |
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{reply 1}<|im_end|> |
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<|im_start|>user |
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{prompt 2}<|im_end|> |
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<|im_start|>assistant |
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(...) |
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``` |
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## Ethical Considerations and Limitations |
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LeoLM has been tested in English and German, and has not covered, nor could it cover all scenarios. |
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For these reasons, as with all LLMs, the potential outputs of `LeoLM/leo-hessianai-7b-chat` cannot be predicted |
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in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses |
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to user prompts. Therefore, before deploying any applications of `LeoLM/leo-hessianai-7b-chat`, developers should |
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perform safety testing and tuning tailored to their specific applications of the model. |
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Please see Meta's [Responsible Use Guide](https://ai.meta.com/llama/responsible-use-guide/). |
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## Dataset Details |
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``` |
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## Stats for 'Subset of OpenAssistant/OASST-DE' (3534 samples (100.0%)) |
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----------------- |
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Accepted: 3534/3534 (100.0%) |
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Accepted tokens: 2259302 |
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Skipped: 0 (0.0%) |
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Min tokens per sample: 29 |
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Max tokens per sample: 2484 |
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Avg tokens per sample: 639.3044708545557 |
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----------------- |
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## Stats for 'Subset of FreedomIntelligence/evol-instruct-deutsch' (57841 samples (100.0%)) |
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----------------- |
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Accepted: 57841/57841 (100.0%) |
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Accepted tokens: 42958192 |
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Skipped: 0 (0.0%) |
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Min tokens per sample: 33 |
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Max tokens per sample: 5507 |
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Avg tokens per sample: 742.6944900675991 |
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----------------- |
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## Stats for 'Subset of FreedomIntelligence/alpaca-gpt4-deutsch' (48969 samples (100.0%)) |
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----------------- |
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Accepted: 48969/48969 (100.0%) |
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Accepted tokens: 13372005 |
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Skipped: 0 (0.0%) |
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Min tokens per sample: 19 |
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Max tokens per sample: 1359 |
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Avg tokens per sample: 273.07082031489307 |
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----------------- |
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## Stats for 'Subset of LeoLM/OpenSchnabeltier' (21314 samples (100.0%)) |
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----------------- |
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Accepted: 21314/21314 (100.0%) |
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Accepted tokens: 8134690 |
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Skipped: 0 (0.0%) |
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Min tokens per sample: 25 |
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Max tokens per sample: 1202 |
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Avg tokens per sample: 381.65947264708643 |
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----------------- |
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## Stats for 'Subset of LeoLM/German_Poems' (490 samples (100.0%)) |
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----------------- |
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Accepted: 490/490 (100.0%) |
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Accepted tokens: 618642 |
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Skipped: 0 (0.0%) |
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Min tokens per sample: 747 |
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Max tokens per sample: 1678 |
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Avg tokens per sample: 1262.534693877551 |
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----------------- |
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## Stats for 'Subset of LeoLM/German_Songs' (392 samples (100.0%)) |
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----------------- |
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Accepted: 392/392 (100.0%) |
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Accepted tokens: 187897 |
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Skipped: 0 (0.0%) |
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Min tokens per sample: 231 |
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Max tokens per sample: 826 |
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Avg tokens per sample: 479.3290816326531 |
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----------------- |
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## Stats for 'total' (132540 samples (100.0%)) |
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----------------- |
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Accepted: 132540/132540 (100.0%) |
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Accepted tokens: 67530728 |
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Skipped: 0 (0.0%) |
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Min tokens per sample: 19 |
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Max tokens per sample: 5507 |
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Avg tokens per sample: 509.51205673758864 |
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----------------- |
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``` |
