93 lines
2.2 KiB
Markdown
93 lines
2.2 KiB
Markdown
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---
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model-index:
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- name: Kulyk-UK-EN
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results:
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- task:
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type: text-generation
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dataset:
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type: facebook/flores
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name: FLORES
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split: devtest
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metrics:
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- type: bleu
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value: 36.27
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name: BLEU
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library_name: transformers
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license: other
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license_name: lfm1.0
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license_link: LICENSE
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language:
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- en
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- uk
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pipeline_tag: text-generation
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tags:
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- liquid
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- lfm2
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- edge
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datasets:
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- lang-uk/FiftyFiveShades
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base_model:
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- LiquidAI/LFM2-350M
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---
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A lightweight model to do machine translation from Ukrainian to English based on recently published LFM2 model. Use [demo](https://huggingface.co/spaces/Yehor/uk-en-translator) to test it.
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Also, there's another model: [kulyk-en-uk](https://huggingface.co/Yehor/kulyk-en-uk)
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**Run with Docker (CPU)**:
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```
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docker run -p 3000:3000 --rm ghcr.io/egorsmkv/kulyk-rust:latest
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```
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**Run using Apptainer (CUDA)**:
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1. Run it using shell:
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```
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apptainer shell --nv ./kulyk.sif
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Apptainer> /opt/entrypoints/kulyk --verbose --n-len 1024 --model-path-ue /project/models/kulyk-uk-en.gguf --model-path-eu /project/models/kulyk-en-uk.gguf
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```
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2. Run it as a webservice:
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```
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apptainer instance start --nv ./kulyk.sif kulyk-ws
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# go to http://localhost:3000
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```
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**Facts**:
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- Fine-tuned with 40M samples (filtered by quality metric) from ~53.5M for 1.4 epochs
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- 354M params
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- Requires 1 GB of RAM to run with bf16
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- BLEU on FLORES-200: 36.27
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- Tokens per second: 229.93 (bs=1), 1664.40 (bs=10), 8392.48 (bs=64)
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- License: lfm1.0
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**Info**:
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- Model name is inherited from name of [Sergiy Kulyk](https://en.wikipedia.org/wiki/Sergiy_Kulyk) who was chargé d'affaires of Ukraine in the United States
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**Training Info**:
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- Learning Rate: 3e-5
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- Learning Rate scheduler type: cosine
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- Warmup Ratio: 0.05
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- Max length: 2048
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- Batch Size: 10
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- `packed=True`
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- Sentences <= 1000 chars
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- Gradient accumulation steps: 4
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- Used Flash Attention 2
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- Time for epoch: 32 hours
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- 2 cards of NVIDIA RTX 3090 Ti (24G)
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- `accelerate` with DeepSpeed
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- Memory usage: 22.212GB-22.458GB
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- torch 2.7.1
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**Acknowledgements**:
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- [Dmytro Chaplynskyi](https://huggingface.co/dchaplinsky) for providing compute to train this model
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- [lang-uk](https://huggingface.co/lang-uk) members for their compilation of different MT datasets
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