How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="radlab/polish-gpt2-medium-v2")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("radlab/polish-gpt2-medium-v2")
model = AutoModelForCausalLM.from_pretrained("radlab/polish-gpt2-medium-v2", device_map="auto")
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Description

This is the polish gpt2 model in medium architecture.

This model was released on 30.11.2023.

Datasets

Data which are used to train this model:

  • clarin-knext/msmarco-pl
  • clarin-knext/nq-pl
  • clarin-knext/hotpotqa-pl
  • clarin-knext/scidocs-pl
  • clarin-knext/nfcorpus-pl
  • clarin-knext/dbpedia-pl
  • clarin-knext/trec-covid-pl
  • clarin-knext/quora-pl
  • clarin-knext/arguana-pl
  • clarin-knext/fiqa-pl
  • radlab/wikipedia-pl
  • radlab/legal-mc4-pl
  • own corpora not published yet

It is about 30,5 GB of data which is 3 times more than the prevoius version.

Metrics from W&B

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Changelog

  • 2023.11.30 - publishing the first version of the model
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Safetensors
Model size
0.4B params
Tensor type
F32
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Datasets used to train radlab/polish-gpt2-medium-v2

Collection including radlab/polish-gpt2-medium-v2