Transformers
TensorBoard
Safetensors
t5
text2text-generation
Trained with AutoTrain
Seq2Seq
Rising World
Java
JavaAPI
text-generation-inference
Instructions to use Andzej-75/flan-t5-RisingWorld-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andzej-75/flan-t5-RisingWorld-code with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Andzej-75/flan-t5-RisingWorld-code") model = AutoModelForSeq2SeqLM.from_pretrained("Andzej-75/flan-t5-RisingWorld-code") - Notebooks
- Google Colab
- Kaggle
| tags: | |
| - autotrain | |
| - text2text-generation | |
| - Seq2Seq | |
| - Rising World | |
| - Java | |
| - JavaAPI | |
| base_model: google/flan-t5-large | |
| widget: | |
| - text: 'Translate to German: My name is Arthur' | |
| example_title: Translation | |
| license: apache-2.0 | |
| datasets: | |
| - google-research-datasets/taskmaster2 | |
| - djaym7/wiki_dialog | |
| - Andzej-75/German_RisingWorld_DPO-prompt-text | |
| - deepmind/code_contests | |
| - openai/gsm8k | |
| - deepmind/aqua_rat | |
| language: | |
| - de | |
| - en | |
| - fr | |
| - multilingual | |
| # Model Trained Using AutoTrain | |
| - Task: Other Text Task => Sequence To Sequence (Seq2Seq) | |
| - Mixed precision: bf16 | |
| - PEFT/LoRA: false | |
| - Quantization: int4 | |
| ## Validation Metrics | |
| * loss: 0.3849843144416809 | |
| * rouge1: 46.2037 | |
| * rouge2: 42.3541 | |
| * rougeL: 45.8784 | |
| * rougeLsum: 45.9787 | |
| * gen_len: 18.9849 | |
| * runtime: 660.9921 | |
| * samples_per_second: 0.401 | |
| * steps_per_second: 0.101 |