# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("iakarshu/latr-base")
model = AutoModelForSeq2SeqLM.from_pretrained("iakarshu/latr-base")Quick Links
latr-base
This model is a fine-tuned version of t5-base on an unknown dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
- Downloads last month
- 15
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="iakarshu/latr-base")