# Model Card for Flan-Alpaca-GPT4-base-3k

This model was obtained by fine-tuning the `google/flan-t5-base` model on the tatsu-lab/alpaca dataset with the max_source_length option set to 3048. The instructions at the following repository were used for fine-tuning: https://github.com/declare-lab/flan-alpaca
The goal of this model was a learning exercise to determine if setting a higher max_source_length resulted in the model interpreting larger prompts during inference. 

### Model Description

- **Language(s) (NLP)**: English
- **Finetuned from model:** google/flan-t5-base

## How to use

```python
from transformers import pipeline

prompt = "Write an email about an alpaca that likes flan"
model = pipeline(model="evolveon/flan-alpaca-gpt4-base-3k")
model(prompt, max_length=3048, do_sample=True)

# Dear AlpacaFriend,
# My name is Alpaca and I'm 10 years old.
# I'm excited to announce that I'm a big fan of flan!
# We like to eat it as a snack and I believe that it can help with our overall growth.
# I'd love to hear your feedback on this idea. 
# Have a great day! 
# Best, AL Paca
```
{"language": ["en"], "license": "apache-2.0", "datasets": ["tatsu-lab/alpaca"]}
transformers pytorch t5 text2text-generation en dataset:tatsu-lab/alpaca license:apache-2.0 autotrain_compatible endpoints_compatible has_space text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #en #dataset-tatsu-lab/alpaca #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 

# Model Card for Flan-Alpaca-GPT4-base-3k

This model was obtained by fine-tuning the 'google/flan-t5-base' model on the tatsu-lab/alpaca dataset with the max_source_length option set to 3048. The instructions at the following repository were used for fine-tuning: URL
The goal of this model was a learning exercise to determine if setting a higher max_source_length resulted in the model interpreting larger prompts during inference. 

### Model Description

- Language(s) (NLP): English
- Finetuned from model: google/flan-t5-base

## How to use


# Model Card for Flan-Alpaca-GPT4-base-3k

This model was obtained by fine-tuning the 'google/flan-t5-base' model on the tatsu-lab/alpaca dataset with the max_source_length option set to 3048. The instructions at the following repository were used for fine-tuning: URL
The goal of this model was a learning exercise to determine if setting a higher max_source_length resulted in the model interpreting larger prompts during inference. ### Model Description

- Language(s) (NLP): English
- Finetuned from model: google/flan-t5-base ## How to use
TAGS
#transformers #pytorch #t5 #text2text-generation #en #dataset-tatsu-lab/alpaca #license-apache-2.0 #autotrain_compatible #endpoints_compatible #has_space #text-generation-inference #region-us 
 # Model Card for Flan-Alpaca-GPT4-base-3k

This model was obtained by fine-tuning the 'google/flan-t5-base' model on the tatsu-lab/alpaca dataset with the max_source_length option set to 3048. The instructions at the following repository were used for fine-tuning: URL
The goal of this model was a learning exercise to determine if setting a higher max_source_length resulted in the model interpreting larger prompts during inference. ### Model Description

- Language(s) (NLP): English
- Finetuned from model: google/flan-t5-base ## How to use