# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("BueormLLC/GPT2Coder")
model = AutoModelForCausalLM.from_pretrained("BueormLLC/GPT2Coder")Quick Links
Model Card
GPT2Coder is a language model that uses openAI's GPT2 model architecture, the model was pre-trained on multiple code data focused on python and languages ​​​​such as Spanish and English.
- It is a pre-trained model in a medium amount of code, so it is not recommended to use it like this, but it is functional and serves uses such as fine tuning and other tasks.
Model Details
- Developed by: BueormAI
- Shared by: BueormLLC
- Model type: Transformer
- Language(s) (NLP): English (en), Spanish (es)
- License: MiT
- Finetuned from model: GPT2 Architecture
Bias, Risks, and Limitations
The model can generate unexpected code and output, in addition to offensive texts and non-functional code.
Recommendations
We recommend using the model with caution and handling its outputs with discretion as they may turn out to be non-functional outputs and harmful and dangerous code.
Training Details
Training Hyperparameters
- Training regime: fp16 mixed precision
- Max_lenght: 1024 tokens
- pretrain epochs: 1 epochs
- finetuning epochs: 2 epochs
Environmental Impact
- Hardware Type: GPU P100
- Hours used: 18 hours
- Cloud Provider: Kaggle
By Bueorm
Thanks to all the people who download and support our projects and manage a vision towards the future with AI, we hope you will support us to continue advancing and launching more followed models.
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Base model
openai-community/gpt2
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="BueormLLC/GPT2Coder")