Instructions to use rohitpanjwani/base_model_ep_20 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohitpanjwani/base_model_ep_20 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rohitpanjwani/base_model_ep_20") model = AutoModelForSeq2SeqLM.from_pretrained("rohitpanjwani/base_model_ep_20", device_map="auto") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Model Name
model_name = "google/flan-t5-base"
Parameter for AutoTokenizer
pad_to_max_length_GD = False
max_length_GD = 64
Parameter for DataCollator
padding_in_datacollator = 'longest'
Training Arguments
batch_size = 4
lr_rate = 1e-5
num_epoch = 20
weight_decay = 0.01
fp16 = False # Make true if GPU is there
predict_with_generate=True
eval_steps = 1000
save_steps = 1000
load_best_model_at_end=True
Generating output
temperature = 1.5
max_len = 256
bum_beam = 50
- Downloads last month
- 6
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support