# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Aityz/reviews_model")
model = AutoModelForCausalLM.from_pretrained("Aityz/reviews_model")Quick Links
reviews_model
This model is a fine-tuned version of aityz/reviews_model 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: 2e-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
- num_epochs: 3.0
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cpu
- Tokenizers 0.13.3
- Downloads last month
- 3
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Aityz/reviews_model")