README.md

---
base_model:
- HuggingFaceTB/SmolLM2-360M
language:
- en
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- safetensors
- onnx
- transformers.js
- pruna-ai
---

# Model Card for davidberenstein1957/SmolLM2-360M-Instruct-smashed

This model was created using the [pruna](https://github.com/PrunaAI/pruna) library. Pruna is a model optimization framework built for developers, enabling you to deliver more efficient models with minimal implementation overhead.

## Usage

First things first, you need to install the pruna library:

```bash
pip install pruna
```

You can [use the transformers library to load the model](https://huggingface.co/davidberenstein1957/SmolLM2-360M-Instruct-smashed?library=transformers) but this might not include all optimizations by default.

To ensure that all optimizations are applied, use the pruna library to load the model using the following code:

```python
from pruna import PrunaModel

loaded_model = PrunaModel.from_pretrained(
    "davidberenstein1957/SmolLM2-360M-Instruct-smashed"
)
```

For inference, you can use the inference methods of the original model like shown [in the original model card](https://huggingface.co/davidberenstein1957/SmolLM2-360M-Instruct-smashed?library=transformers). Alternatively, you can visit the full documentation [here](https://pruna.readthedocs.io/en/latest/index.html) for more information.

## Smash Configuration

The compression configuration of the model is stored in the `smash_config.json` file, which describes the optimization methods that were applied to the model.

```bash
{
    "batcher": null,
    "cacher": null,
    "compiler": null,
    "factorizer": null,
    "pruner": null,
    "quantizer": "torchao",
    "torchao_excluded_modules": "none",
    "torchao_quant_type": "int8dq",
    "batch_size": 1,
    "device": "cpu",
    "device_map": null,
    "save_fns": [
        "save_before_apply"
    ],
    "load_fns": [
        "transformers"
    ],
    "reapply_after_load": {
        "factorizer": null,
        "pruner": null,
        "quantizer": "torchao",
        "cacher": null,
        "compiler": null,
        "batcher": null
    }
}
```

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