93 lines
5.8 KiB
ReStructuredText
93 lines
5.8 KiB
ReStructuredText
.. meta::
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:google-site-verification: S66K6GAclKw1RroxU0Rka_2d1LZFVe27M0gRneEsIVI
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BigDL: fast, distributed, secure AI for Big Data
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=================================================
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Latest News
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---------------------------------
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- **Try the latest** `bigdl-llm <https://github.com/intel-analytics/BigDL/tree/main/python/llm>`_ **library for running LLM (large language model) on your Intel laptop using INT4 with very low latency!** [*]_. *(It is built on top of the excellent work of* `llama.cpp <https://github.com/ggerganov/llama.cpp>`_, `gptq <https://github.com/IST-DASLab/gptq>`_, `bitsandbytes <https://github.com/TimDettmers/bitsandbytes>`_, *etc., and supports any Hugging Face Transformers model.)*
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- **[Update] Over a dozen models have been verified on** `bigdl-llm <https://github.com/intel-analytics/BigDL/tree/main/python/llm>`_, including *LLaMA/LLaMA2, ChatGLM/ChatGLM2, MPT, Falcon, Dolly-v1/Dolly-v2, StarCoder, Whisper, QWen, Baichuan,* and more; see the complete list `here <https://github.com/intel-analytics/BigDL/tree/main/python/llm/README.md#verified-models>`_.
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------
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Overview
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---------------------------------
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`BigDL <https://github.com/intel-analytics/bigdl>`_ seamlessly scales your data analytics & AI applications from laptop to cloud, with the following libraries:
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- `LLM <https://github.com/intel-analytics/BigDL/tree/main/python/llm>`_: Low-bit (INT3/INT4/INT5/INT8) large language model library for Intel CPU/GPU
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- `Orca <doc/Orca/index.html>`_: Distributed Big Data & AI (TF & PyTorch) Pipeline on Spark and Ray
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- `Nano <doc/Nano/index.html>`_: Transparent Acceleration of Tensorflow & PyTorch Programs on Intel CPU/GPU
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- `DLlib <doc/DLlib/index.html>`_: "Equivalent of Spark MLlib" for Deep Learning
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- `Chronos <doc/Chronos/index.html>`_: Scalable Time Series Analysis using AutoML
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- `Friesian <doc/Friesian/index.html>`_: End-to-End Recommendation Systems
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- `PPML <doc/PPML/index.html>`_: Secure Big Data and AI (with SGX Hardware Security)
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------
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Choosing the right BigDL library
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---------------------------------
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.. graphviz::
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digraph BigDLDecisionTree {
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graph [pad=0.1 ranksep=0.3 tooltip=" "]
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node [color="#0171c3" shape=box fontname="Arial" fontsize=14 tooltip=" "]
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edge [tooltip=" "]
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Feature1 [label="Hardware Secured Big Data & AI?"]
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Feature2 [label="Python vs. Scala/Java?"]
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Feature3 [label="What type of application?"]
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Feature4 [label="Domain?"]
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LLM[href="https://github.com/intel-analytics/BigDL/blob/main/python/llm" target="_blank" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-LLM document"]
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Orca[href="../doc/Orca/index.html" target="_blank" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Orca document"]
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Nano[href="../doc/Nano/index.html" target="_blank" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Nano document"]
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DLlib1[label="DLlib" href="../doc/DLlib/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-DLlib document"]
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DLlib2[label="DLlib" href="../doc/DLlib/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-DLlib document"]
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Chronos[href="../doc/Chronos/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Chronos document"]
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Friesian[href="../doc/Friesian/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Friesian document"]
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PPML[href="../doc/PPML/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-PPML document"]
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ArrowLabel1[label="No" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel2[label="Yes" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel3[label="Python" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel4[label="Scala/Java" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel5[label="Large Language Model" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel6[label="Big Data + \n AI (TF/PyTorch)" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel7[label="Accelerate \n TensorFlow / PyTorch" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel8[label="DL for Spark MLlib" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel9[label="High Level App Framework" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel10[label="Time Series" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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ArrowLabel11[label="Recommender System" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
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Feature1 -> ArrowLabel1[dir=none]
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ArrowLabel1 -> Feature2
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Feature1 -> ArrowLabel2[dir=none]
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ArrowLabel2 -> PPML
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Feature2 -> ArrowLabel3[dir=none]
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ArrowLabel3 -> Feature3
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Feature2 -> ArrowLabel4[dir=none]
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ArrowLabel4 -> DLlib1
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Feature3 -> ArrowLabel5[dir=none]
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ArrowLabel5 -> LLM
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Feature3 -> ArrowLabel6[dir=none]
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ArrowLabel6 -> Orca
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Feature3 -> ArrowLabel7[dir=none]
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ArrowLabel7 -> Nano
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Feature3 -> ArrowLabel8[dir=none]
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ArrowLabel8 -> DLlib2
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Feature3 -> ArrowLabel9[dir=none]
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ArrowLabel9 -> Feature4
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Feature4 -> ArrowLabel10[dir=none]
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ArrowLabel10 -> Chronos
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Feature4 -> ArrowLabel11[dir=none]
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ArrowLabel11 -> Friesian
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}
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------
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.. [*] Performance varies by use, configuration and other factors. `bigdl-llm` may not optimize to the same degree for non-Intel products. Learn more at www.Intel.com/PerformanceIndex.
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