dice-research
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lola_v1

Text Generation

Transformers

Safetensors

lola_v1

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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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-## Uses
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 ## How to Get Started with the Model
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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.
+- **Developed by:** DICE Research Group (https://dice-research.org/) @ Paderborn University (https://www.uni-paderborn.de/)
+- **Model type:** GPT2 style (decoder-only) with Mixture-of-Experts layers
+- **Language(s) (NLP):** 160+
+- **License:** Coming soon
+- **Repository:** https://github.com/dice-group/LOLA-Megatron-DeepSpeed
 ## How to Get Started with the Model
+This pre-trained (causal language modeling) model can only be used for text-generation and requires further fine-tuning on downstream tasks.
+### How to use
+You can use this model directly with a pipeline for text generation.
+```python
+>>> from transformers import pipeline
+>>> generator = pipeline('text-generation', model="dice-research/lola_v1", trust_remote_code=True)
+>>> generator("The quick brown fox", max_length=13)
+[{'generated_text': 'The quick brown fox jumps over the lazy dog.'}]
+```
+To use the top-k sampling, please set `do_sample` to `True`.
+**Note:** The tokenizer used in the model comes from mGPT (https://github.com/ai-forever/mgpt)
+## Training Details
+### Training Framework
+- DeepSpeed Megatron (https://github.com/microsoft/Megatron-DeepSpeed)
+- Architecture type: Transformers (Decoder-only) with Mixture-of-Experts (MoE)
+- Number of Experts: 16
+- Model Size: 1.3 Billion Dense / 7.4 Billion Sparse
+### Pretraining Dataset
+- CulturaX (https://huggingface.co/datasets/uonlp/CulturaX)
+- Total Tokens: 6.3 Trillion
+- Total Languages: 167
+### LOLA v1 Training:
+- Computing cluster: Noctua2 (https://pc2.uni-paderborn.de/hpc-services/available-systems/noctua2)
+- Number of GPUs: 96x Nvidia A100 (40GB)
+- Training steps: 296000
+- Tokens consumed: 465 Billion
+- Training time: ~19 days