BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model
We introduce the Bittensor Language Model, called "BTLM-3B-8K", a new
state-of-the-art 3 billion parameter open-source language model. BTLM-3B-8K was
trained on 627B tokens from the SlimPajama dataset with a mixture of 2,048 and
8,192 context lengths. BTLM-3B-8K outperforms all existing 3B parameter models
by 2-5.5% across downstream tasks. BTLM-3B-8K is even competitive with some 7B
parameter models. Additionally, BTLM-3B-8K provides excellent long context
performance, outperforming MPT-7B-8K and XGen-7B-8K on tasks up to 8,192
context length. We trained the model on a cleaned and deduplicated SlimPajama
dataset; aggressively tuned the \textmu P hyperparameters and schedule; used
ALiBi position embeddings; and adopted the SwiGLU nonlinearity.
  On Hugging Face, the most popular models have 7B parameters, indicating that
users prefer the quality-size ratio of 7B models. Compacting the 7B parameter
model to one with 3B parameters, with little performance impact, is an
important milestone. BTLM-3B-8K needs only 3GB of memory with 4-bit precision
and takes 2.5x less inference compute than 7B models, helping to open up access
to a powerful language model on mobile and edge devices. BTLM-3B-8K is
available under an Apache 2.0 license on Hugging Face:
https://huggingface.co/cerebras/btlm-3b-8k-base.
650d015be2c7c01fc1a62765
Nolan Dey
admin_assigned
2023-09-22T15:29:02.892Z
62c47a267877fdc687c613da
https://cdn-avatars.huggingface.co/v1/production/uploads/62c47a267877fdc687c613da/G0uoHHgEuND3Ro5zU1Kk5.jpeg
Nolan Dey
user
ndey96
650d015be2c7c01fc1a62766
Daria Soboleva
admin_assigned
2023-09-22T15:29:50.231Z
6414bbe095fb6f824b2035a5
https://cdn-avatars.huggingface.co/v1/production/uploads/1679080567124-6414bbe095fb6f824b2035a5.jpeg
Daria Soboleva
user
daria-soboleva
650d015be2c7c01fc1a62767
Faisal Al-Khateeb
admin_assigned
2023-09-22T15:29:57.959Z
6419da12b4adb0e101b22ac3
https://cdn-avatars.huggingface.co/v1/production/uploads/6419da12b4adb0e101b22ac3/mI4FjJCcgv4vDQvmXlFrm.jpeg
Faisal Al-khateeb
user
faisalak
650d015be2c7c01fc1a62768
Bowen Yang
admin_assigned
2023-09-22T15:30:20.855Z
64c4e59619565937fb279a94
/avatars/201c31460110d4d8e5f5896ff920e382.svg
Bowen Yang
user
Bowenyang-online
650d015be2c7c01fc1a62769
Ribhu Pathria
650d015be2c7c01fc1a6276a
Hemant Khachane
650d015be2c7c01fc1a6276b
Shaheer Muhammad
650d015be2c7c01fc1a6276c
Zhiming
650d015be2c7c01fc1a6276d
Chen
650d015be2c7c01fc1a6276e
Robert Myers
admin_assigned
2023-09-22T15:31:44.102Z
6132c6c146a28b5058423152
https://cdn-avatars.huggingface.co/v1/production/uploads/6132c6c146a28b5058423152/uCf-HNZnG3CNo9mNwzgQ-.jpeg
Rob Myers
user
robertmyers
650d015be2c7c01fc1a6276f
Jacob Robert Steeves
650d015be2c7c01fc1a62770
Natalia Vassilieva
admin_assigned
2023-09-22T15:32:16.718Z
6410072c208821a59b780fcb
https://cdn-avatars.huggingface.co/v1/production/uploads/6410072c208821a59b780fcb/R9ZDtB9KIaNrLmM2b0GKc.png
Natalia Vassilieva
user
vnata
650d015be2c7c01fc1a62771
Marvin Tom
650d015be2c7c01fc1a62772
Joel Hestness
admin_assigned
2023-09-22T15:32:34.195Z
643433124b34368fdb02e8b0
https://cdn-avatars.huggingface.co/v1/production/uploads/643433124b34368fdb02e8b0/mnBzw2JSHk0I5vXGY-YVI.jpeg
Joel Hestness
user
jthestness
BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model
We introduce the Bittensor Language Model, called "BTLM-3B-8K", a new
state-of-the-art 3 billion parameter open-source language model. BTLM-3B-8K was
trained on 627B tokens from the SlimPajama dataset with a mixture of 2,048 and
8,192 context lengths. BTLM-3B-8K outperforms all existing 3B parameter models
by 2-5.5% across downstream tasks. BTLM-3B-8K is even competitive with some 7B
parameter models. Additionally, BTLM-3B-8K provides excellent long context
performance, outperforming MPT-7B-8K and XGen-7B-8K on tasks up to 8,192
context length. We trained the model on a cleaned and deduplicated SlimPajama
dataset; aggressively tuned the \textmu P hyperparameters and schedule; used
ALiBi position embeddings; and adopted the SwiGLU nonlinearity.
  On Hugging Face, the most popular models have 7B parameters, indicating that
users prefer the quality-size ratio of 7B models. Compacting the 7B parameter
model to one with 3B parameters, with little performance impact, is an
important milestone. BTLM-3B-8K needs only 3GB of memory with 4-bit precision
and takes 2.5x less inference compute than 7B models, helping to open up access
to a powerful language model on mobile and edge devices. BTLM-3B-8K is
available under an Apache 2.0 license on Hugging Face:
https://huggingface.co/cerebras/btlm-3b-8k-base.
BTLM-3B-8K, a state-of-the-art 3 billion parameter open-source language model, outperforms existing 3B models and rivals 7B models, offering excellent long context performance and reduced memory and inference compute requirements.
ALiBi position embeddings SwiGLU nonlinearity BTLM-3B-8K SlimPajama dataset parameter-efficiency long context performance MPT-7B-8K XGen-7B-8K Hugging Face