metadata
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: flan-t5-small-distil-v2
results: []
language:
- en
flan-t5-small-distil-v2
This model is a fine-tuned version of google/flan-t5-small 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: 0.0005
- train_batch_size: 128
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Use
CPU
Click to expand
# pip install -q transformers
from transformers import pipeline
checkpoint = "{model_name}"
model = pipeline('text2text-generation', model=checkpoint, use_auth_token=True)
input_prompt = 'Please let me know your thoughts on the given place and why you think it deserves to be visited: \n"Barcelona, Spain"'
generated_text = generator(input_prompt, max_length=512, do_sample=True, repetition_penalty=1.5)[0]['generated_text']
print("Response": generated_text)
GPU
Click to expand
# pip install -q transformers
from transformers import pipeline
checkpoint = "{model_name}"
model = pipeline('text2text-generation', model=checkpoint, use_auth_token=True, device=0)
input_prompt = 'Please let me know your thoughts on the given place and why you think it deserves to be visited: \n"Barcelona, Spain"'
generated_text = generator(input_prompt, max_length=512, do_sample=True, repetition_penalty=1.5)[0]['generated_text']
print("Response": generated_text)
Framework versions
- Transformers 4.27.0
- Pytorch 2.0.0+cu117
- Datasets 2.2.0
- Tokenizers 0.13.2