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: