| https://huggingface.co/HuggingFaceM4/tiny-random-LlamaForCausalLM | |
| ```python | |
| from sparseml.transformers import SparseAutoModelForCausalLM, SparseAutoTokenizer, oneshot | |
| from sparseml.modifiers import SparseGPTModifier | |
| model_id = "HuggingFaceM4/tiny-random-LlamaForCausalLM" | |
| compressed_model_id = "mgoin/tiny-random-LlamaForCausalLM-pruned95-compressed" | |
| # Apply SparseGPT to the model | |
| oneshot( | |
| model=model_id, | |
| dataset="open_platypus", | |
| recipe=SparseGPTModifier(sparsity=0.95), | |
| output_dir="temp-output", | |
| ) | |
| model = SparseAutoModelForCausalLM.from_pretrained("temp-output", torch_dtype="auto") | |
| tokenizer = SparseAutoTokenizer.from_pretrained(model_id) | |
| model.save_pretrained(compressed_model_id.split("/")[-1], save_compressed=True) | |
| tokenizer.save_pretrained(compressed_model_id.split("/")[-1]) | |
| # Upload the checkpoint to Hugging Face | |
| from huggingface_hub import HfApi | |
| HfApi().upload_folder( | |
| folder_path=compressed_model_id.split("/")[-1], | |
| repo_id=compressed_model_id, | |
| ) | |
| ``` |