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Releases Β· Oneflow-Inc/libai Β· GitHub
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Releases: Oneflow-Inc/libai
Releases Β· Oneflow-Inc/libai
LiBai v0.3.0 Release
1185ad9
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v0.3.0 (03/11/2024)
New Features:
- Support mock transformers, see Mock transformers
- Support lm-evaluation-harness for model evaluation
- User Experience Optimization
New Supported Models:
- These models are natively supported by libai
| Models | 2D(tp+pp) Inference | 3D Parallel Training |
|---|---|---|
| BLOOM | β | - |
| ChatGLM | β | β |
| Couplets | β | β |
| DALLE2 | β | - |
| Llama2 | β | β |
| MAE | β | β |
| Stable_Diffusion | - | - |
New Mock Models:
- These models are extended and implemented by libai through mocking transformers.
| Models | Tensor Parallel | Pipeline Parallel |
|---|---|---|
| BLOOM | β | - |
| GPT2 | β | - |
| LLAMA | β | - |
| LLAMA2 | β | - |
| Baichuan | β | - |
| OPT | β | - |
Assets 2
LiBai v0.2.0 Release
8fd79ee
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v0.2.0 (07/07/2022)
New Features:
- Support evaluation enabled and set
eval_iter - Support customized sampler in
config.py - Support rdma for pipeline-model-parallel
- Support multi fused kernel
- fused_scale_mask_softmax_dropout
- fused_scale_tril_softmax_mask_scale
- fused_self_attention in branch
libai_bench
- User Experience Optimization
- Optimization for training throughput, see benchmark for more details
New Supported Models:
Assets 2
4 people reacted
LiBai v0.1.0 Release
ba20850
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Some major features:
- Data Parallelism
- 1D Tensor Parallelism
- Pipeline Parallelism
- Unified Distributed Layers for single-GPU and multi-GPU
- "LazyConfig" system for more flexible syntax and no predefined structures
- Easy-to-use trainer and engine
- CV & NLP Data Preprocessing
- Mixed Precision Training
- Activation Checkpointing
- Gradient Accumulation
- Gradient Clipping
- Zero Redundancy Optimizer (ZeRO)
Model_Zoo
- Bert (3D Parallelism)
- GPT-2 (3D Parallelism)
- ViT (3D Parallelism)
- Swin-Transformer (data parallelism)
- Add finetune task in
projects/ - Add text classification in
projects
Assets 2
4 people reacted
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