metadata
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
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:
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: