Apple OpenELM: An Efficient Language Model Family with Open Training and Inference Framework

162 Pulls Updated 6 weeks ago

6 weeks ago

a1245824de01 · 2.2GB

model
openelm
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3.04B
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Q5_K_M
template
{{- if .System }} <|system|> {{ .System }} </s> {{- end }} <|user|> {{ .Prompt }} </s> <|assistant|>
system
You are a helpful assistant. Perform the task to the best of your ability.
params
{"num_ctx":2048,"stop":["<|system|>","<|user|>","<|assistant|>","</s>","<s>"],"temperature":0.3}
license
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Readme

OpenELM: An Efficient Language Model Family with Open Training and Inference Framework

Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, Mohammad Rastegari

We introduce OpenELM, a family of Open Efficient Language Models. OpenELM uses a layer-wise scaling strategy to efficiently allocate parameters within each layer of the transformer model, leading to enhanced accuracy. We pretrained OpenELM models using the CoreNet library. We release both pretrained and instruction tuned models with 270M, 450M, 1.1B and 3B parameters. We release the complete framework, encompassing data preparation, training, fine-tuning, and evaluation procedures, alongside multiple pre-trained checkpoints and training logs, to facilitate open research.

Our pre-training dataset contains RefinedWeb, deduplicated PILE, a subset of RedPajama, and a subset of Dolma v1.6, totaling approximately 1.8 trillion tokens. Please check license agreements and terms of these datasets before using them.

(from: https://huggingface.co/apple/OpenELM-3B-Instruct)

Model conversion by https://huggingface.co/SanctumAI/OpenELM-3B-Instruct-GGUF