math-lm
mesh-transformer-jax
| math-lm | mesh-transformer-jax | |
|---|---|---|
| 2 | 52 | |
| 977 | 6,213 | |
| 3.6% | - | |
| 8.4 | 0.0 | |
| about 2 months ago | over 1 year ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
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math-lm
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Large Language Models: Compairing Gen2/Gen3 Models (GPT-3, GPT-J, MT5 and More)
The training material is named The Pile, a 800GB large corpus consisting of 22 different sources, including scientific research papers from ArXiV, legal documents from the the FreeLaw Project, and eBooks from Project Gutenberg campus. As shown in its documentation, GPT-J performance is on par with the GPT-3 6B model. Also, the model can be used for advanced theorem proving and natural language understanding.
- Llemma: An open language model for mathematics
mesh-transformer-jax
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Large Language Models: Compairing Gen2/Gen3 Models (GPT-3, GPT-J, MT5 and More)
GPT-J is a LLM case study with two goals: Training a LLM with a data source containing unique material, and using the training frameworkMesh Transformer JAX to achieve a high training efficiency through parallelization. There is no research paper about GPT-J, but on its GitHub pages, the model, different checkpoints, and the complete source code for training is given.
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[R] Parallel Attention and Feed-Forward Net Design for Pre-training and Inference on Transformers
This idea has already been proposed in ViT-22B and GPT-J-6B.
- Show HN: Finetune LLaMA-7B on commodity GPUs using your own text
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[D] An Instruct Version Of GPT-J Using Stanford Alpaca's Dataset
Sure. Here's the repo I used for the fine-tuning: https://github.com/kingoflolz/mesh-transformer-jax. I used 5 epochs, and appart from that I kept the default parameters in the repo.
- Boss wants me to use ChatGPT for work, but I refuse to input my personal phone number. Any advice?
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Let's build GPT: from scratch, in code, spelled out by Andrej Karpathy
You can skip to step 4 using something like GPT-J as far as I understand: https://github.com/kingoflolz/mesh-transformer-jax#links
The pretrained model is already available.
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Best coding model?
The Github repo suggests it's possible you can change the number of checkpoints to make it run on a GPU.
- Ask HN: What language models can I fine-tune at home?
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selfhosted/ open-source ChatGPT alternative?
GPT-J, which uses mesh-transformer-jax: https://github.com/kingoflolz/mesh-transformer-jax
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GPT-J, an open-source alternative to GPT-3
They hinted at it in the screenshot, but the goods are linked from the https://6b.eleuther.ai page: https://github.com/kingoflolz/mesh-transformer-jax#gpt-j-6b (Apache 2)
What are some alternatives?
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
tensorflow - An Open Source Machine Learning Framework for Everyone
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
KoboldAI-Client
alpaca-lora - Instruct-tune LLaMA on consumer hardware
Finetune_LLMs - Repo for fine-tuning Casual LLMs
gpt-2 - Code for the paper "Language Models are Unsupervised Multitask Learners"
cedille-ai - ✒️ Cedille is a large French language model (6B), released under an open-source license
replika-research - Replika.ai Research Papers, Posters, Slides & Datasets
swarm-jax - Swarm training framework using Haiku + JAX + Ray for layer parallel transformer language models on unreliable, heterogeneous nodes
gpt-neox - An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library.