
# T5-Reverse (T5R)

This model can generate prompts (instructions) for any text!

This model is an instruction-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on [alpaca dataset](https://huggingface.co/datasets/tatsu-lab/alpaca) but in **reverse format**!

## How to Use the Model

You can use the `transformers` library to load and utilize the T5-Reverse (T5R) model for generating prompts based on text. Here's an example of how to do it:

```python
>>> # Import required libraries
>>> import torch
>>> from transformers import pipeline

>>> # Load the model and tokenizer using the pipeline from Hugging Face Hub
>>> inference = pipeline("text2text-generation", model="kargaranamir/T5R-base")

>>> # Example instruction and prompt
>>> sample = '''
>>> Instruction: X
>>> Output: 1- Base your meals on higher fibre starchy carbohydrates. 2- Eat lots of fruit and veg. 3- Eat more fish, including a portion of oily fish.
>>> What kind of instruction could this be the answer to?
>>> X:
>>> '''

>>> # Generate a response using the model
>>> res = inference(sample)

>>> # Print the generated response
>>> print(res)

[{'generated_text': 'Instruction: Generate three recommendations for a healthy diet.'}]
```


## Citation

If you find this model/approach useful, make a link to the huggingface model.
{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer", "text2text-generation"], "datasets": ["tatsu-lab/alpaca"], "pipeline_tag": "text2text-generation", "widget": [{"text": "Instruction: X\nOutput: Adolf Hitler (German: [\u02c8ad\u0254lf \u02c8h\u026atl\u0250] (listen); 20 April 1889 \u2013 30 April 1945) was an Austrian-born German politician who was the dictator of Germany from 1933 until his suicide in 1945. He rose to power as the leader of the Nazi Party,[a] becoming the chancellor in 1933 and then taking the title of F\u00fchrer und Reichskanzler in 1934.[b] During his dictatorship, he initiated World War II in Europe by invading Poland on 1 September 1939. He was closely involved in military operations throughout the war and was central to the perpetration of the Holocaust: the genocide of about six million Jews and millions of other victims.\nX:\n", "example_title": "Example 1"}, {"text": "Instruction: X\nOutput: 1- Base your meals on higher fibre starchy carbohydrates. 2- Eat lots of fruit and veg. 3- Eat more fish, including a portion of oily fish.\nWhat kind of instruction could this be the answer to?\nX:\n", "example_title": "Example 2"}], "model-index": [{"name": "T5R-base", "results": []}]}
transformers pytorch safetensors t5 text2text-generation generated_from_trainer en dataset:tatsu-lab/alpaca license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #en #dataset-tatsu-lab/alpaca #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


# T5-Reverse (T5R)

This model can generate prompts (instructions) for any text!

This model is an instruction-tuned version of google/flan-t5-base on alpaca dataset but in reverse format!

## How to Use the Model

You can use the 'transformers' library to load and utilize the T5-Reverse (T5R) model for generating prompts based on text. Here's an example of how to do it:




If you find this model/approach useful, make a link to the huggingface model.
# T5-Reverse (T5R)

This model can generate prompts (instructions) for any text!

This model is an instruction-tuned version of google/flan-t5-base on alpaca dataset but in reverse format! ## How to Use the Model

You can use the 'transformers' library to load and utilize the T5-Reverse (T5R) model for generating prompts based on text. Here's an example of how to do it:




If you find this model/approach useful, make a link to the huggingface model.
TAGS
#transformers #pytorch #safetensors #t5 #text2text-generation #generated_from_trainer #en #dataset-tatsu-lab/alpaca #license-mit #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # T5-Reverse (T5R)

This model can generate prompts (instructions) for any text!

This model is an instruction-tuned version of google/flan-t5-base on alpaca dataset but in reverse format! ## How to Use the Model

You can use the 'transformers' library to load and utilize the T5-Reverse (T5R) model for generating prompts based on text. Here's an example of how to do it:




If you find this model/approach useful, make a link to the huggingface model.