transformers safetensors t5 text2text-generation trl ppo reinforcement-learning summarization license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
license: apache-2.0
pipeline_tag: summarization
tags:
- trl
- ppo
- transformers
- reinforcement-learning
---

# TRL Model

This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
 guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.

## Usage

To use this model for inference, first install the TRL library:

```bash
python -m pip install trl
```

You can then generate text as follows:

```python
from transformers import pipeline

generator = pipeline("text-generation", model="IrwinD//tmp/tmpoz9k3o9o/IrwinD/log_sage_ppo_model")
outputs = generator("Hello, my llama is cute")
```

If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:

```python
from transformers import AutoTokenizer
from trl import AutoModelForCausalLMWithValueHead

tokenizer = AutoTokenizer.from_pretrained("IrwinD//tmp/tmpoz9k3o9o/IrwinD/log_sage_ppo_model")
model = AutoModelForCausalLMWithValueHead.from_pretrained("IrwinD//tmp/tmpoz9k3o9o/IrwinD/log_sage_ppo_model")

inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
outputs = model(**inputs, labels=inputs["input_ids"])
```