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Model: dbmdz/german-gpt2-faust
Source: Original Platform

.gitattributes

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+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+language: de
+
+widget:
+- text: "Schon um die Liebe"
+
+license: mit
+---
+
+# German GPT-2 model
+
+In this repository we release (yet another) GPT-2 model, that was trained on various texts for German.
+
+The model is meant to be an entry point for fine-tuning on other texts, and it is definitely not as good or "dangerous" as the English GPT-3 model. We do not plan extensive PR or staged releases for this model 😉
+
+**Note**: The model was initially released under an anonymous alias (`anonymous-german-nlp/german-gpt2`) so we now "de-anonymize" it.
+
+More details about GPT-2 can be found in the great [Hugging Face](https://huggingface.co/transformers/model_doc/gpt2.html) documentation.
+
+## German GPT-2 fine-tuned on Faust I and II
+
+We fine-tuned our German GPT-2 model on "Faust I and II" from Johann Wolfgang Goethe. These texts can be obtained from [Deutsches Textarchiv (DTA)](http://www.deutschestextarchiv.de/book/show/goethe_faust01_1808). We use the "normalized" version of both texts (to avoid out-of-vocabulary problems with e.g. "ſ")
+
+Fine-Tuning was done for 100 epochs, using a batch size of 4 with half precision on a RTX 3090. Total time was around 12 minutes (it is really fast!).
+
+We also open source this fine-tuned model. Text can be generated with:
+
+```python
+from transformers import pipeline
+
+pipe = pipeline('text-generation', model="dbmdz/german-gpt2-faust",
+                 tokenizer="dbmdz/german-gpt2-faust")   
+
+text = pipe("Schon um die Liebe", max_length=100)[0]["generated_text"]
+
+print(text)
+```
+
+and could output:
+
+```
+Schon um die Liebe bitte ich, Herr! Wer mag sich die dreifach Ermächtigen?
+Sei mir ein Held!
+Und daß die Stunde kommt spreche ich nicht aus.
+Faust (schaudernd).
+Den schönen Boten finde' ich verwirrend;
+```
+
+# License
+
+All models are licensed under [MIT](LICENSE).
+
+# Huggingface model hub
+
+All models are available on the [Huggingface model hub](https://huggingface.co/dbmdz).
+
+# Contact (Bugs, Feedback, Contribution and more)
+
+For questions about our BERT models just open an issue
+[here](https://github.com/stefan-it/german-gpt/issues/new) 🤗
+
+# Acknowledgments
+
+Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC).
+Thanks for providing access to the TFRC ❤️
+
+Thanks to the generous support from the [Hugging Face](https://huggingface.co/) team,
+it is possible to download both cased and uncased models from their S3 storage 🤗

config.json

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+{
+  "_name_or_path": "anonymous-german-nlp/german-gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 52000,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 52000,
+  "gradient_checkpointing": false,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "resid_pdrop": 0.1,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "vocab_size": 52001
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

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tokenizer_config.json

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