metadata
license: mit
widget:
- example_title: Question Answering!
text: 'Please Answer the Question: what is depression?'
- example_title: Other Example!
text: 'Please Answer the Question: How to bake a cake?'
- example_title: Other Example!
text: 'Please Answer the Question: what is depression?'
- example_title: Other Example!
text: >-
Please Answer the Question: I'm going through some things with my
feelings and myself.I barely sleep and I do nothing but think about how
I'm worthless and how I shouldn't be here. I've never tried or
contemplated suicide. I've always wanted to fix my issues, but I never get
around to it. How can I change my feeling of being worthless to everyone?
inference:
parameters:
do_sample: true
max_new_tokens: 250
datasets:
- databricks/databricks-dolly-15k
- VMware/open-instruct
MaxMini-Instruct-248M
Overview
MaxMini-Instruct-248M is a T5 (Text-To-Text Transfer Transformer) model Instruct fine-tuned on a variety of tasks. This model is designed to perform a range of instruction tasks.
Model Details
- Model Name: MaxMini-Instruct-248M
- Model Type: T5 (Text-To-Text Transfer Transformer)
- Model Size: 248M parameters
- Instruction Tuning
Usage
Installation
You can install the model via the Hugging Face library:
pip install transformers
pip install torch
Inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("suriya7/MaxMini-Instruct-248M")
model = AutoModelForSeq2SeqLM.from_pretrained("suriya7/MaxMini-Instruct-248M")
my_question = "what is depression?"
inputs = "Please answer to this question: " + my_question
inputs = tokenizer(inputs, return_tensors="pt"
)
generated_ids = model.generate(**inputs, max_new_tokens=250,do_sample=True)
decoded = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
print(f"Generated Output: {decoded}")