43 lines
1.6 KiB
Markdown
43 lines
1.6 KiB
Markdown
---
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language: fa
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tags:
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- text-generation
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widget:
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- text: "در یک اتفاق شگفت انگیز، پژوهشگران"
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- text: "گرفتگی بینی در کودکان و بهخصوص نوزادان باعث میشود"
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- text: "امیدواریم نوروز امسال سالی"
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---
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# GPT2 Medium 4 Persian
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> This is part of the
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[Flax/Jax Community Week](https://discuss.huggingface.co/t/pretrain-gpt2-from-scratch-in-persian/7560), organized by [HuggingFace](https://huggingface.co/) and TPU usage sponsored by Google.
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## Team Members
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- [Mehrdad Farahani](huggingface.co/m3hrdadfi)
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- [Saied Alimoradi](https://discuss.huggingface.co/u/saied)
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- [M. Reza Zerehpoosh](huggingface.co/ironcladgeek)
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- [Hooman Sedghamiz](https://discuss.huggingface.co/u/hooman650)
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- [Mazeyar Moeini Feizabadi](https://discuss.huggingface.co/u/mazy1998)
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## Dataset
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We used [Oscar](https://huggingface.co/datasets/oscar) dataset, which is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus.
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## How To Use
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You can use this model directly with a pipeline for text generation.
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```python
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from transformers import pipeline, AutoTokenizer, GPT2LMHeadModel
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tokenizer = AutoTokenizer.from_pretrained('flax-community/gpt2-medium-persian')
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model = GPT2LMHeadModel.from_pretrained('flax-community/gpt2-medium-persian')
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generator = pipeline('text-generation', model, tokenizer=tokenizer, config={'max_length':100})
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generated_text = generator('در یک اتفاق شگفت انگیز، پژوهشگران')
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```
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For using Tensorflow import TFGPT2LMHeadModel instead of GPT2LMHeadModel.
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## Demo
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... SOON
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## Evaluation
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... SOON |