Reinforcement Learning
Transformers
Safetensors
gpt2
text-generation
trl
ppo
text-generation-inference
Instructions to use Amogh06/PPO-FFT-SafeGenAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amogh06/PPO-FFT-SafeGenAI with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Amogh06/PPO-FFT-SafeGenAI") model = AutoModelForCausalLM.from_pretrained("Amogh06/PPO-FFT-SafeGenAI") - Notebooks
- Google Colab
- Kaggle
File size: 1,373 Bytes
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license: apache-2.0
library_name: transformers
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="Amogh06//home/amogh-am/PhD/llama3_DMD_interpretability/SafeGenAI_assignments/PPO/FFT")
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("Amogh06//home/amogh-am/PhD/llama3_DMD_interpretability/SafeGenAI_assignments/PPO/FFT")
model = AutoModelForCausalLMWithValueHead.from_pretrained("Amogh06//home/amogh-am/PhD/llama3_DMD_interpretability/SafeGenAI_assignments/PPO/FFT")
inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
outputs = model(**inputs, labels=inputs["input_ids"])
```
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