| --- |
| language: en |
| tags: |
| - autotrain |
| - text-generation |
| - llm |
| - memes |
| library_name: transformers |
| library_version: [latest version at the time of training] |
| model_type: llama 2 |
| widget: |
| - text: "When you try to code without coffee, " |
| --- |
| |
| # Llama 2 Meme Generator |
|
|
| ## Model Description |
|
|
| This model is a fine-tuned version of the `llama 2` model, specifically tailored for generating meme captions. It captures the essence and humor commonly found in popular internet memes and offers a unique approach to meme creation. Just provide a prompt or a meme context, and let the model generate a fitting caption! |
|
|
| ## Training Data |
|
|
| The model was trained using a diverse dataset of meme captions, spanning various internet trends, jokes, and pop culture references. This ensures a wide range of meme generation capabilities, from classic meme formats to contemporary internet humor. |
|
|
| ## Training Procedure |
|
|
| The model was fine-tuned using the `autotrain llm` command with optimal hyperparameters for meme generation. Special care was taken to avoid overfitting, ensuring the model can generalize well across various meme contexts. |
|
|
| ## Usage |
|
|
| To generate a meme caption using this model, you can use the following code: |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelWithLMHead |
| |
| tokenizer = AutoTokenizer.from_pretrained("bickett/meme-llama") |
| model = AutoModelWithLMHead.from_pretrained("bickett/meme-llama") |
| |
| input_text = "When you try to code without coffee" |
| input_ids = tokenizer.encode(input_text, return_tensors="pt") |
| output = model.generate(input_ids) |
| |
| print(tokenizer.decode(output[0], skip_special_tokens=True)) |
| |
