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0.0.14.1 genz_llm-0.0.14.1-py3-none-any.whl

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Project: genz-llm
Version: 0.0.14.1
Filename: genz_llm-0.0.14.1-py3-none-any.whl
Download: [link]
Size: 47479
MD5: 616ce6f28700efc5e9d5277941fe1cae
SHA256: 16501f6325614d9d02d705ff9b56908f75c04686519d594d18ff67b7ed9529b9
Uploaded: 2024-10-30 02:08:04 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: genz_llm
Version: 0.0.14.1
Summary: GenZ is designed to simplify the relationship between the hardware platform used for serving Large Language Models(LLMs) and inference serving metrics like latency and memory.
Author-Email: Abhimanyu Bambhaniya <abambhaniya3[at]gatech.edu>
Project-Url: Homepage, https://github.com/abhibambhaniya/GenZ-LLM-Analyzer
Project-Url: Issues, https://github.com/abhibambhaniya/GenZ-LLM-Analyzer/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Requires-Dist: matplotlib (>=3.8.0)
Requires-Dist: kaleido (>=0.2.1)
Requires-Dist: nbformat (>=5.9.2)
Requires-Dist: numpy (>=1.26.3)
Requires-Dist: pandas (>=2.2.1)
Requires-Dist: paretoset (>=1.2.3)
Requires-Dist: pillow (>=10.2.0)
Requires-Dist: plotly (>=5.9.0)
Requires-Dist: tqdm (>=4.66.2)
Requires-Dist: ipywidgets
Requires-Dist: seaborn
Requires-Dist: plotnine
Requires-Dist: Jinja2
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 4012 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.3.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
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GenZ/analyse_model.py sha256=p-hncXRuxQIL0V4RySWVUyQAv0brnvO8o6Xk3EErTKM 11703
GenZ/collective_times.py sha256=Q3CidUxvR7RPyR2yZocJ8drJ_qbHjVUQMZkqMwYdM1w 3037
GenZ/operator_base.py sha256=mYeTMRPEDaR2xy-N8B5h1hNTJgREo-QmBk3wxxcyHCw 13705
GenZ/operators.py sha256=qPE-hg8fYRWe1EH0jbjQ7_imuWqOxrRvpYIimM_OQE8 12139
GenZ/parallelism.py sha256=4mhT8CLN5ENHTfbs99YTzxHSgwDqGnaBqYCPJkMwnmk 1125
GenZ/system.py sha256=wGjOLSyCnKNrGaVytARuh9-tO9XzD5JefuRNYH6WtI8 5123
GenZ/unit.py sha256=TBxfNjovFAfHO7QF405E9xee9mnjgqCBZgWSM9CWl2o 1894
GenZ/version.py sha256=SxvRes_80c-42zwvn5BXPvpGVs_EZ69FUEtUBF1k9Ts 23
GenZ/Astra_sim/fix_chakra_traces.py sha256=KUXIby13cruuxUKz7JTgW1VWQCPmcv4Cz-5ii_nGp0I 4257
GenZ/Astra_sim/get_astra_sim_time.py sha256=VhtKIAYGjmGkOm2z7xPRJrx1dXVeilNOy9YrLhc6VhM 7849
GenZ/LLM_inference/__init__.py sha256=oBb8xDEDPMDqlgxOOiJGkpN4c446IjLHvnqzbKl-HSQ 345
GenZ/LLM_inference/best_parallelization.py sha256=q5vVBPFEwx87mT9MuYeYEW9hUBdh62UcTtrel2BFfCY 5918
GenZ/LLM_inference/llm_decode.py sha256=uPErwrvu4E7VFjVmIawF8oSEEfMcS6PiNqoHgR81Png 7249
GenZ/LLM_inference/llm_prefill.py sha256=FQYPGECkhfL-LUU63ga6Lw7JXIlourKFsNWmnosSsPM 6788
GenZ/LLM_inference/platform_size.py sha256=U1RRdStHOYBi8Ip-7mptDwJZZZUBWcLaQBJUmpnynTY 2112
GenZ/LLM_inference/utils.py sha256=zzpzgN2hDpkH3DJbxKIDveLsUqCbv9lr6bc-pPL1rmo 3770
GenZ/Models/__init__.py sha256=SNktkdApSCYXu8_YfZySUNUBqaLdvFnVX71kXjbnpkk 410
GenZ/Models/attention.py sha256=IUhscEeIUKdzTczeTTv2snR8JJQJ232l_a7QNQVRgf8 3359
GenZ/Models/default_models.py sha256=WuKPYo6cuCu6HXspVLwZTUwa4GAUKAei75NVxlZSQQk 8258
GenZ/Models/embedding.py sha256=QvTNDhcbQSBMg2E4Fpjorxsgp1dpzoDfYc_c9btj1Bs 1380
GenZ/Models/ffn.py sha256=VuvLA08XG-5yPWjOyOCag0A0vH2BtSiUWBUYkNs7doY 5979
GenZ/Models/get_language_model.py sha256=fBKyC1embPT6gbN47jD2flPCm9IqfXPGql_Nv_ei4Bk 8511
GenZ/Models/mamba.py sha256=pvJY50Scj9fX09WqRK4zYKFEFqgIOkVe7m0Ql0b0QRI 5130
GenZ/Models/utils.py sha256=Px2x2kT1PEn1pFTS0nqGB1NaSGFSJa32P8RgKBKgXhQ 1622
GenZ/Models/Model_sets/alibaba.py sha256=iyvH9GfDnUo6NvRksdsLpvQnUmlqxMPF0Xxoa6pLFYY 7512
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GenZ/Models/Model_sets/meta.py sha256=nU-oU9LFWuM5Ez4StGdymhbxlA0MfASK7-szO2NQ5AA 6888
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GenZ/Models/Model_sets/nvidia.py sha256=ZeVaTrLmlNEo1Z1qP8jvScNUh0RnbKBKcY702VAHwnw 1920
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genz_llm-0.0.14.1.dist-info/RECORD — —

top_level.txt

GenZ
Systems