Buckets:
| # Quickstart | |
| ## Export | |
| You can export your 🤗 Transformers models to ExecuTorch easily: | |
| ```bash | |
| optimum-cli export executorch --model meta-llama/Llama-3.2-1B --recipe xnnpack --output_dir meta_llama3_2_1b_executorch | |
| ``` | |
| ## Inference | |
| To load a model and run inference, you can just replace your `AutoModelForCausalLM` class with the corresponding `ExecuTorchModelForCausalLM` class. You can also load a PyTorch checkpoint and convert it to ExecuTorch on-the-fly when loading your model. | |
| ```diff | |
| - from transformers import AutoModelForCausalLM | |
| + from optimum.executorch import ExecuTorchModelForCausalLM | |
| from transformers import AutoTokenizer | |
| model_id = "meta-llama/Llama-3.2-1B" | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| - model = AutoModelForCausalLM.from_pretrained(model_id) | |
| + model = ExecuTorchModelForCausalLM.from_pretrained(model_id) | |
| ``` |
Xet Storage Details
- Size:
- 868 Bytes
- Xet hash:
- 75028743db9900fdaeb9687c1d47fa25ba2c3a632783e9650d74bec9d38caed4
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