## LuxGPT-2 

GPT-2 model for Text Generation in luxembourgish language, trained on 667 MB of text data, consisting of RTL.lu news articles, comments, parlament speeches, the luxembourgish Wikipedia, Newscrawl, Webcrawl and subtitles.
The training took place on a 32 GB Nvidia Tesla V100
- with an initial learning rate of 5e-5
- with Batch size 4
- for 109 hours
- for 30 epochs
- using the transformers library
<br/>
more detailed training information can be found in the "trainer_state.json".  

## Usage
```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("laurabernardy/LuxGPT2")

model = AutoModelForCausalLM.from_pretrained("laurabernardy/LuxGPT2")
```

## Limitations and Biases

See the [GPT2 model card](https://huggingface.co/gpt2) for considerations on limitations and bias. See the [GPT2 documentation](https://huggingface.co/transformers/model_doc/gpt2.html) for details on GPT2.

{"language": ["lb"], "license": "mit", "tags": ["luxembourgish", "l\u00ebtzebuergesch", "text generation"], "model-index": [{"name": "LuxGPT2", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "Luxembourgish Test Dataset", "type": "LuxembourgishTestDataset"}, "metrics": [{"type": "accuracy", "value": "0.33"}, {"type": "perplexity", "value": "46.69"}]}]}]}
transformers pytorch safetensors gpt2 text-generation luxembourgish lëtzebuergesch text generation lb license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #luxembourgish #lëtzebuergesch #text generation #lb #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

## LuxGPT-2 

GPT-2 model for Text Generation in luxembourgish language, trained on 667 MB of text data, consisting of URL news articles, comments, parlament speeches, the luxembourgish Wikipedia, Newscrawl, Webcrawl and subtitles.
The training took place on a 32 GB Nvidia Tesla V100
- with an initial learning rate of 5e-5
- with Batch size 4
- for 109 hours
- for 30 epochs
- using the transformers library
<br/>
more detailed training information can be found in the "trainer_state.json".  

## Usage


## Limitations and Biases

See the GPT2 model card for considerations on limitations and bias. See the GPT2 documentation for details on GPT2.

## LuxGPT-2 

GPT-2 model for Text Generation in luxembourgish language, trained on 667 MB of text data, consisting of URL news articles, comments, parlament speeches, the luxembourgish Wikipedia, Newscrawl, Webcrawl and subtitles.
The training took place on a 32 GB Nvidia Tesla V100
- with an initial learning rate of 5e-5
- with Batch size 4
- for 109 hours
- for 30 epochs
- using the transformers library
<br/>
more detailed training information can be found in the "trainer_state.json". ## Usage ## Limitations and Biases

See the GPT2 model card for considerations on limitations and bias. See the GPT2 documentation for details on GPT2.
TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #luxembourgish #lëtzebuergesch #text generation #lb #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ## LuxGPT-2 

GPT-2 model for Text Generation in luxembourgish language, trained on 667 MB of text data, consisting of URL news articles, comments, parlament speeches, the luxembourgish Wikipedia, Newscrawl, Webcrawl and subtitles.
The training took place on a 32 GB Nvidia Tesla V100
- with an initial learning rate of 5e-5
- with Batch size 4
- for 109 hours
- for 30 epochs
- using the transformers library
<br/>
more detailed training information can be found in the "trainer_state.json". ## Usage ## Limitations and Biases

See the GPT2 model card for considerations on limitations and bias. See the GPT2 documentation for details on GPT2.
passage: TAGS
#transformers #pytorch #safetensors #gpt2 #text-generation #luxembourgish #lëtzebuergesch #text generation #lb #license-mit #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
## LuxGPT-2 

GPT-2 model for Text Generation in luxembourgish language, trained on 667 MB of text data, consisting of URL news articles, comments, parlament speeches, the luxembourgish Wikipedia, Newscrawl, Webcrawl and subtitles.
The training took place on a 32 GB Nvidia Tesla V100
- with an initial learning rate of 5e-5
- with Batch size 4
- for 109 hours
- for 30 epochs
- using the transformers library
<br/>
more detailed training information can be found in the "trainer_state.json".## Usage## Limitations and Biases

See the GPT2 model card for considerations on limitations and bias. See the GPT2 documentation for details on GPT2.