license: apache-2.0 | |
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="nteku1//tmp/tmpu05xwfmf/nteku1/Jon_GPT2L_PPO_epi_point1") | |
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("nteku1//tmp/tmpu05xwfmf/nteku1/Jon_GPT2L_PPO_epi_point1") | |
model = AutoModelForCausalLMWithValueHead.from_pretrained("nteku1//tmp/tmpu05xwfmf/nteku1/Jon_GPT2L_PPO_epi_point1") | |
inputs = tokenizer("Hello, my llama is cute", return_tensors="pt") | |
outputs = model(**inputs, labels=inputs["input_ids"]) | |
``` | |