[model_cards] antoiloui/belgpt2 🇧🇪 (#7166)

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model_cards/antoiloui/belgpt2/README.md

+---
+language: "fr"
+---
+
+# BelGPT-2
+
+**BelGPT-2** (*Belgian GPT-2* 🇧🇪) is a "small" GPT-2 model pre-trained on a very large and heterogeneous French corpus (around 60Gb). Please check [antoiloui/gpt2-french](https://github.com/antoiloui/gpt2-french) for more information about the pre-trained model, the data, the code to use the model and the code to pre-train it.
+
+
+## Using BelGPT-2 for Text Generation in French
+
+You can use BelGPT-2 with [🤗 transformers](https://github.com/huggingface/transformers) library as follows:
+
+```python
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+# Load pretrained model and tokenizer
+model = GPT2LMHeadModel.from_pretrained("antoiloui/belgpt2")
+tokenizer = GPT2Tokenizer.from_pretrained("antoiloui/belgpt2")
+
+# Generate a sample of text
+model.eval()
+output = model.generate(
+            bos_token_id=random.randint(1,50000),
+            do_sample=True,   
+            top_k=50, 
+            max_length=100,
+            top_p=0.95, 
+            num_return_sequences=1
+)
+
+# Decode it
+decoded_output = []
+for sample in output:
+    decoded_output.append(tokenizer.decode(sample, skip_special_tokens=True))
+print(decoded_output)
+```
+
+## Data
+
+Below is the list of all French copora used to pre-trained the model:
+
+| Dataset | `$corpus_name` | Raw size | Cleaned size |
+| :------|   :--- | :---: | :---: | 
+| CommonCrawl |  `common_crawl`   |  200.2 GB   |  40.4 GB   |
+| NewsCrawl |   `news_crawl`  |   10.4 GB  |  9.8 GB   |
+| Wikipedia |   `wiki`  |   19.4 GB  |  4.1 GB   |
+| Wikisource |   `wikisource`  |  4.6  GB  |  2.3 GB   |
+| Project Gutenberg |  `gutenberg`   |  1.3 GB   |  1.1 GB   |
+| EuroParl |  `europarl`   |  289.9 MB   |   278.7 MB  |
+| NewsCommentary |  `news_commentary`   |   61.4 MB  |  58.1 MB   |
+| **Total** |     |   **236.3 GB**  |  **57.9 GB**   |