Transformers
Safetensors
Polish
t5
text2text-generation
seq2seq
text-to-text
scientific-language-models
cross-lingual-transfer
wechsel
global-mmlu
text-generation-inference
Instructions to use rausch/pl-t5-base-sci-cp-15k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rausch/pl-t5-base-sci-cp-15k with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rausch/pl-t5-base-sci-cp-15k") model = AutoModelForSeq2SeqLM.from_pretrained("rausch/pl-t5-base-sci-cp-15k") - Notebooks
- Google Colab
- Kaggle
| { | |
| "source_type": "checkpoint", | |
| "original_checkpoint": "/netscratch/nrauscher/projects/BA-hydra/cross_lingual_transfer_multilingual/logs/train_hf_monolingual/pol_Latn/runs/2026-02-14_03-02-55/checkpoints/best/step-014000-val_ppl-5.65309.ckpt", | |
| "tokenizer_path": "allegro/plt5-base", | |
| "hydra_config": "/netscratch/nrauscher/projects/BA-hydra/cross_lingual_transfer_multilingual/logs/train_hf_monolingual/pol_Latn/runs/2026-02-14_03-02-55/.hydra/config.yaml", | |
| "base_model": "allegro/plt5-base", | |
| "vocab_from_state": 50048, | |
| "missing_keys": [], | |
| "unexpected_keys": [] | |
| } |