Decilm 6b Instruct

🚀 DeciLM 6B-Instruct

DeciLM 6B-Instruct is a model designed for short-form instruction following. It addresses the need for efficient instruction processing in English language tasks, offering both commercial and research value.

🚀 Quick Start

Use the following code to start using the model:

# pip install -q transformers

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

checkpoint = "Deci/DeciLM-6b-instruct"
device = "cuda" # for GPU usage or "cpu" for CPU usage

tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModelForCausalLM.from_pretrained(checkpoint, torch_dtype=torch.bfloat16, trust_remote_code=True).to(device)

inputs = tokenizer.encode("How do I make french toast? Think through it step by step", return_tensors="pt").to(device)
outputs = model.generate(inputs, max_new_tokens=100, do_sample=True, top_p=0.95)
print(tokenizer.decode(outputs[0]))

✨ Features

• Commercial and Research Use: Suitable for both commercial applications and research purposes in English, and can be fine - tuned for other languages.
• Fast Training: Trained using advanced proprietary methodologies with the SlimPijamas dataset, enabling fast training.
• Fine - Tuned: Further fine - tuned on a subset of the OpenOrca dataset to create DeciLM-6B-Instruct.

📦 Installation

The installation command is included in the quick start code:

# pip install -q transformers

📚 Documentation

Model Information

Model Sources

• Paper: DeciLM 6B Technical Blog
• Demo: DeciLM 6B - Instruct Demo
• Notebook: DeciLM 6B - Instruct Notebook

Uses

The model is intended for commercial and research use in English and can be fine - tuned for use in other languages.

Training Details

DeciLM 6B was trained using the SlimPijamas dataset with advanced proprietary methods for fast training. It was further fine - tuned on a subset of the OpenOrca dataset to create DeciLM-6B-Instruct.

Evaluation

Runtime Benchmarks

• Throughput (tokens/sec) - Measured with optimal batch - PyTorch BS 64, Infery LLM BS 128
• In order to replicate the results of the PyTorch benchmark, use this code example

Disclaimer

DeciLM 6B - Instruct has not been aligned for safety or trained using RLHF.

How to Cite

Please cite this model using the following format:

@misc{DeciFoundationModels,
title = {DeciLM 6B Instruct},
author = {DeciAI Research Team},
year = {2023}
url={[https://huggingface.co/Deci/DeciLM-6b-instruct](https://huggingface.co/Deci/DeciLM-6b-instruct)},
}