#llama2 — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #llama2, aggregated by home.social.
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Title: P6: CTO mistakes and distributed training of NN [2023-09-19 Tue]
completion of this period, after one month and a half.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P6: CTO mistakes and distributed training of NN [2023-09-19 Tue]
completion of this period, after one month and a half.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P6: CTO mistakes and distributed training of NN [2023-09-19 Tue]
completion of this period, after one month and a half.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P6: CTO mistakes and distributed training of NN [2023-09-19 Tue]
completion of this period, after one month and a half.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P5: CTO mistakes and distributed training of NN [2023-09-19 Tue]
planning, verifying assumptions, presenting a beautiful and clear result to management.
8) Forced one person to report to three different individuals.
9) Set two conflicting goals: a tight deadline of September 30 and small
meaningless goals.
10) Named a probationary period one month and firing after successeful\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P5: CTO mistakes and distributed training of NN [2023-09-19 Tue]
planning, verifying assumptions, presenting a beautiful and clear result to management.
8) Forced one person to report to three different individuals.
9) Set two conflicting goals: a tight deadline of September 30 and small
meaningless goals.
10) Named a probationary period one month and firing after successeful\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P5: CTO mistakes and distributed training of NN [2023-09-19 Tue]
planning, verifying assumptions, presenting a beautiful and clear result to management.
8) Forced one person to report to three different individuals.
9) Set two conflicting goals: a tight deadline of September 30 and small
meaningless goals.
10) Named a probationary period one month and firing after successeful\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P5: CTO mistakes and distributed training of NN [2023-09-19 Tue]
planning, verifying assumptions, presenting a beautiful and clear result to management.
8) Forced one person to report to three different individuals.
9) Set two conflicting goals: a tight deadline of September 30 and small
meaningless goals.
10) Named a probationary period one month and firing after successeful\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P4: CTO mistakes and distributed training of NN [2023-09-19 Tue]
5) Did not create a roadmap and did not discuss it with everyone.
6) Did not pay attention to the collected information on the research project and did not
consider its importance in planning.
7) Assigned multiple responsibilities to one person: gathering information, programming,\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P4: CTO mistakes and distributed training of NN [2023-09-19 Tue]
5) Did not create a roadmap and did not discuss it with everyone.
6) Did not pay attention to the collected information on the research project and did not
consider its importance in planning.
7) Assigned multiple responsibilities to one person: gathering information, programming,\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P4: CTO mistakes and distributed training of NN [2023-09-19 Tue]
5) Did not create a roadmap and did not discuss it with everyone.
6) Did not pay attention to the collected information on the research project and did not
consider its importance in planning.
7) Assigned multiple responsibilities to one person: gathering information, programming,\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P4: CTO mistakes and distributed training of NN [2023-09-19 Tue]
5) Did not create a roadmap and did not discuss it with everyone.
6) Did not pay attention to the collected information on the research project and did not
consider its importance in planning.
7) Assigned multiple responsibilities to one person: gathering information, programming,\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P2: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) Hired people with different skills and abilities and organized competition between them
instead of building a team.
4) Demanded strict adherence to deadlines on a research project.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P2: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) Hired people with different skills and abilities and organized competition between them
instead of building a team.
4) Demanded strict adherence to deadlines on a research project.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P2: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) Hired people with different skills and abilities and organized competition between them
instead of building a team.
4) Demanded strict adherence to deadlines on a research project.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P2: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) Hired people with different skills and abilities and organized competition between them
instead of building a team.
4) Demanded strict adherence to deadlines on a research project.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P1: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) Did not introduce employees to each other, so nobody knew what each person was capable of.
2) Appointed leaders without explaining their responsibilities.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P1: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) Did not introduce employees to each other, so nobody knew what each person was capable of.
2) Appointed leaders without explaining their responsibilities.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P1: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) Did not introduce employees to each other, so nobody knew what each person was capable of.
2) Appointed leaders without explaining their responsibilities.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P1: P3: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) Did not introduce employees to each other, so nobody knew what each person was capable of.
2) Appointed leaders without explaining their responsibilities.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P2: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) you should create a list of your and your boss mistakes every
day or week to have measure of danger.
4) you need half of the year to get good reputation yourself before you can work freely.
5) explain your approach to work to head to be understood, and adapt to head.Here is a list of mistakes of head of company:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
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Title: P2: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) you should create a list of your and your boss mistakes every
day or week to have measure of danger.
4) you need half of the year to get good reputation yourself before you can work freely.
5) explain your approach to work to head to be understood, and adapt to head.Here is a list of mistakes of head of company:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
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Title: P2: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) you should create a list of your and your boss mistakes every
day or week to have measure of danger.
4) you need half of the year to get good reputation yourself before you can work freely.
5) explain your approach to work to head to be understood, and adapt to head.Here is a list of mistakes of head of company:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
-
Title: P2: CTO mistakes and distributed training of NN [2023-09-19 Tue]
3) you should create a list of your and your boss mistakes every
day or week to have measure of danger.
4) you need half of the year to get good reputation yourself before you can work freely.
5) explain your approach to work to head to be understood, and adapt to head.Here is a list of mistakes of head of company:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
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Title: P1: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) you should not write wiki until you 100hure, that you will not be fired,
they will not value it anyway.
2) in subordination it is necessary to perform closes and far task 100 percent
and 100 percent clearly indicate 1. when and 2. what will be at the and.
Or you will be fired no matter what.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P1: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) you should not write wiki until you 100hure, that you will not be fired,
they will not value it anyway.
2) in subordination it is necessary to perform closes and far task 100 percent
and 100 percent clearly indicate 1. when and 2. what will be at the and.
Or you will be fired no matter what.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P1: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) you should not write wiki until you 100hure, that you will not be fired,
they will not value it anyway.
2) in subordination it is necessary to perform closes and far task 100 percent
and 100 percent clearly indicate 1. when and 2. what will be at the and.
Or you will be fired no matter what.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P1: CTO mistakes and distributed training of NN [2023-09-19 Tue]
1) you should not write wiki until you 100hure, that you will not be fired,
they will not value it anyway.
2) in subordination it is necessary to perform closes and far task 100 percent
and 100 percent clearly indicate 1. when and 2. what will be at the and.
Or you will be fired no matter what.\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management -
Title: P0: CTO mistakes and distributed training of NN [2023-09-19 Tue]
I found out, that distributed training of neural networks require very
low latency between nodes. It is required to use better network equipment and
adjustments to network settings to get better training speed
than at single machine, and bigger batches of course.I have been fired in one month and 2 weeks and I learned that:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
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Title: P0: CTO mistakes and distributed training of NN [2023-09-19 Tue]
I found out, that distributed training of neural networks require very
low latency between nodes. It is required to use better network equipment and
adjustments to network settings to get better training speed
than at single machine, and bigger batches of course.I have been fired in one month and 2 weeks and I learned that:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
-
Title: P0: CTO mistakes and distributed training of NN [2023-09-19 Tue]
I found out, that distributed training of neural networks require very
low latency between nodes. It is required to use better network equipment and
adjustments to network settings to get better training speed
than at single machine, and bigger batches of course.I have been fired in one month and 2 weeks and I learned that:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
-
Title: P0: CTO mistakes and distributed training of NN [2023-09-19 Tue]
I found out, that distributed training of neural networks require very
low latency between nodes. It is required to use better network equipment and
adjustments to network settings to get better training speed
than at single machine, and bigger batches of course.I have been fired in one month and 2 weeks and I learned that:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 #management
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Title: P2: Distributed training [2023-09-15 Fri]
and automatically shard layers (multi-node training).
⛏
Best links about distributed training paredigms:
1. https://huggingface.co/docs/transformers/v4.17.0/en/parallelism
2. https://lilianweng.github.io/posts/2021-09-25-train-large/
3. comparision of distributed ml systems https://arxiv.org/pdf/1909.02061.pdf⚰\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2
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Title: P2: Distributed training [2023-09-15 Fri]
and automatically shard layers (multi-node training).
⛏
Best links about distributed training paredigms:
1. https://huggingface.co/docs/transformers/v4.17.0/en/parallelism
2. https://lilianweng.github.io/posts/2021-09-25-train-large/
3. comparision of distributed ml systems https://arxiv.org/pdf/1909.02061.pdf⚰\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2
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Title: P2: Distributed training [2023-09-15 Fri]
and automatically shard layers (multi-node training).
⛏
Best links about distributed training paredigms:
1. https://huggingface.co/docs/transformers/v4.17.0/en/parallelism
2. https://lilianweng.github.io/posts/2021-09-25-train-large/
3. comparision of distributed ml systems https://arxiv.org/pdf/1909.02061.pdf⚰\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2
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Title: P2: Distributed training [2023-09-15 Fri]
and automatically shard layers (multi-node training).
⛏
Best links about distributed training paredigms:
1. https://huggingface.co/docs/transformers/v4.17.0/en/parallelism
2. https://lilianweng.github.io/posts/2021-09-25-train-large/
3. comparision of distributed ml systems https://arxiv.org/pdf/1909.02061.pdf⚰\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2
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Title: P1: Distributed training [2023-09-15 Fri]
- Huggingface/accelerate with DeepSpeed or Megatron-LM
- FairScale by Meta, facebook
- Megatron-LM by Nvidia
- DeepSpeed by Microsoft
- Horovod Uber
- Ray
- ColossalAI
- PyTorch Lightning
- FFCV: Fast Forward Computer Vision
⛧
I have made distributed training of ResNet50 in FSDP, the new PyTorch distribute
training approach allow to train modes that not fit to one GPU\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 -
Title: P1: Distributed training [2023-09-15 Fri]
- Huggingface/accelerate with DeepSpeed or Megatron-LM
- FairScale by Meta, facebook
- Megatron-LM by Nvidia
- DeepSpeed by Microsoft
- Horovod Uber
- Ray
- ColossalAI
- PyTorch Lightning
- FFCV: Fast Forward Computer Vision
⛧
I have made distributed training of ResNet50 in FSDP, the new PyTorch distribute
training approach allow to train modes that not fit to one GPU\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 -
Title: P1: Distributed training [2023-09-15 Fri]
- Huggingface/accelerate with DeepSpeed or Megatron-LM
- FairScale by Meta, facebook
- Megatron-LM by Nvidia
- DeepSpeed by Microsoft
- Horovod Uber
- Ray
- ColossalAI
- PyTorch Lightning
- FFCV: Fast Forward Computer Vision
⛧
I have made distributed training of ResNet50 in FSDP, the new PyTorch distribute
training approach allow to train modes that not fit to one GPU\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 -
Title: P1: Distributed training [2023-09-15 Fri]
- Huggingface/accelerate with DeepSpeed or Megatron-LM
- FairScale by Meta, facebook
- Megatron-LM by Nvidia
- DeepSpeed by Microsoft
- Horovod Uber
- Ray
- ColossalAI
- PyTorch Lightning
- FFCV: Fast Forward Computer Vision
⛧
I have made distributed training of ResNet50 in FSDP, the new PyTorch distribute
training approach allow to train modes that not fit to one GPU\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 -
Title: P1: P0: Distributed training [2023-09-15 Fri]
This week, I was reading about frameworks that help to scale
the training of transformers and other architectures to multiple nodes,
mostly for the PyTorch framework. ☃️
Here is a list that I composed:\n#nn #ai #neural #automl #tensorflow #tf #torch #pytorch #llama #llama2 -
Claude will embrace the gospel of #OSS just like #meta did after source for #Llama2 weights were leaked
@carnage4life https://mas.to/@carnage4life/116330826619059254
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CW: Artificial text - On few occasion it's also funny. Meow
Introducing 'Papillitise Portraits!' We professionally photograph your favourite papillitises & frame them for all to admire. Think of the bragging rights! #papillitises #art #oddlysatisfying
#BusinessIdea #Business #Ai #Llm #LlaMA2 -
CW: Artificial text - On few occasion it's also funny. Meow
Introducing 'Glacial Gains,' a service that harvests snowmelt runoff from ski slopes & sells it as artisanal bottled water! 'Purely pristine', we say, while ignoring the questionable mountain funk. 🧊💧 #snowmelt #artisanalwater #weirdbusiness
#BusinessIdea #Business #Ai #Llm #LlaMA2
