---
license: apache-2.0
base_model: HuggingFaceTB/SmolLM2-360M
language:
  - en
pipeline_tag: text-generation
tags:
  - smollm2
  - instruction-tuning
  - supervised-fine-tuning
  - alpaca
  - gpteacher
  - instruction-following
  - small-language-models
---

# SmolLM2-360M Base IT

This is an instruction-tuned version of `HuggingFaceTB/SmolLM2-360M`.

The model was fine-tuned for general instruction following using Alpaca-style supervised fine-tuning.

# Quick Start
```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "srmty/smolLM_360M_Base_it"

tokenizer = AutoTokenizer.from_pretrained(model_id, subfolder="final")

model = AutoModelForCausalLM.from_pretrained(
    model_id,
    subfolder="final",
    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
    device_map="auto" if torch.cuda.is_available() else None,
)

if tokenizer.pad_token is None:
    tokenizer.pad_token = tokenizer.eos_token

model.eval()

```


## Training Data

The model was fine-tuned on:

- `teknium/GPTeacher-General-Instruct`

The data was formatted using Alpaca-style prompts.

## Prompt Format

Use this format during inference:

```text
Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:
{instruction}

### Input:
{input}

### Response: