The fastest way to fork and deploy open-source AI.

For anyone annoyed with Amazon's (and Azure's and Google's) gatekeeping on their cloud GPU VMs, I recommend @runpod_io None of the 'prove you really need this much power' bs from the majors Just great pricing, availability, and an intuitive UI

Apparently, we got a Kaggle silver medal in the @arcprize for being in position 17th out of 1430 teams 🙃 I wish I had more time to spend on it; we worked on it for a couple of weeks for fun with limited compute (HUGE thanks to @runpod_io!)

ai engineering is just tweaking config values in a notebook until you run out of runpod credits

Runpod has great prices as well

I have been testing work with @runpod_io last 2 weeks and I've to say the service is pretty amazing. Super awesome UX and DevEX (and plenty of GPU backend choices). It's about ~20% pricier than Lambda labs, but worth it IMO given all the harness and workflow they provide that Lambda doesn't. I'm not associated with them in any way or manner, btw. Just a very happy customer.

Thanks @runpod_io, loving all of the updates! 👀

thank u runpod i was doing a training run for work when GCP and cloudflare died 🙏🙏 i appreciate u staying online it finished successfully

i'm a big fan of @runpod_io they're most reliable GPU provider for training and running your models at scale

I'm proud to be part of the GPU Elite, awarded by @runpod_io 😍

Just discovered @runpod_io 🤯🤯🤯 Per second billing for serverless GPU capacity?! Infinitely scalable?! Whaaaat

@runpod_io is so goated, first time trying it today and it’s super easy to setup + their ai helper on discord was very helpful If you ever need cpus/gpus I recommend it!

Why is Huggingface not adding Runpod as a serverless provider? Runpod is 10-15x cheaper for serverless deployment than AWS and GCP

Needed a GPU for a quick job, didn't want to commit to anything long-term. Runpod was perfect for that. Love that I can just spin one up and shut it down after.

Trained a 7B parameter model in just 90 minutes for $0.80 using LoRA + Runpod. Yes, it’s possible—and no, you don’t need enterprise hardware.

Runpod support > lambdalabs support. For on demand GPUs runpod still works the best ime

Runpod > Sagemaker, VertexAi, AzureML

The @runpod_io event was amazing! One reason we can boast about fast speeds at @jigsawstack is because the cold boot on runpod GPUs is basically nonexistent!

Axolotl works out of the box with @runpod_io's Clusters. It's as easy as running this on each node using the Docker images that we ship.

Shoutout to @runpod_io as I work through my first non-trivial machine learning experiment. They have exactly what you need if you're a hobbyist and their prices are about a fifth of the big cloud providers.

1.3k spent on the training run, this latest release would not have been possible without runpod

🏃 Runpod is now available on SkyPilot! ✈️ Get high-end GPUs (3x cheaper) with great availability: sky launch --gpus H100 Great thanks to @runpod_io for contributing this integration to join the Sky!

Introducing SmolLlama! An effort to make a mini-ChatGPT from scratch! Its based on the Llama (123 M) structure I coded and pre-trained on 10B tokens (10k steps) from the FineWeb dataset from scratch using DDP (torchrun) in PyTorch. Used 2xH100 (SXM) 80GB VRAM from Runpod

I love runpod

switching from runpod+cursor to colab made my ml pipeline setup 100x faster, but i'm missing access to claude sonnet 3.7 for interpreting repo files & terminal outputs. need a way to either: 1. connect cursor to colab so the llm sees my terminal outputs 2. efficiently feed colab outputs to an llm without tedious copy/paste what's the best workflow for llm-assisted debugging when your code runs in colab but your preferred assistant lacks context? any MCP servers to give cursor access to colab?

Introducing SmolLlama! An effort to make a mini-ChatGPT from scratch! Its based on the Llama (123 M) structure I coded and pre-trained on 10B tokens (10k steps) from the FineWeb dataset from scratch using DDP (torchrun) in PyTorch. Used 2xH100 (SXM) 80GB VRAM from Runpod

Shoutout to @runpod_io as I work through my first non-trivial machine learning experiment. They have exactly what you need if you're a hobbyist and their prices are about a fifth of the big cloud providers.

Apparently, we got a Kaggle silver medal in the @arcprize for being in position 17th out of 1430 teams 🙃 I wish I had more time to spend on it; we worked on it for a couple of weeks for fun with limited compute (HUGE thanks to @runpod_io!)

I'm proud to be part of the GPU Elite, awarded by @runpod_io 😍

Why is Huggingface not adding Runpod as a serverless provider? Runpod is 10-15x cheaper for serverless deployment than AWS and GCP

Needed a GPU for a quick job, didn't want to commit to anything long-term. Runpod was perfect for that. Love that I can just spin one up and shut it down after.

thank u runpod i was doing a training run for work when GCP and cloudflare died 🙏🙏 i appreciate u staying online it finished successfully

I have been testing work with @runpod_io last 2 weeks and I've to say the service is pretty amazing. Super awesome UX and DevEX (and plenty of GPU backend choices). It's about ~20% pricier than Lambda labs, but worth it IMO given all the harness and workflow they provide that Lambda doesn't. I'm not associated with them in any way or manner, btw. Just a very happy customer.

i'm a big fan of @runpod_io they're most reliable GPU provider for training and running your models at scale

Runpod has great prices as well

@runpod_io is so goated, first time trying it today and it’s super easy to setup + their ai helper on discord was very helpful If you ever need cpus/gpus I recommend it!

Runpod support > lambdalabs support. For on demand GPUs runpod still works the best ime

1.3k spent on the training run, this latest release would not have been possible without runpod

Axolotl works out of the box with @runpod_io's Clusters. It's as easy as running this on each node using the Docker images that we ship.

Just discovered @runpod_io 🤯🤯🤯 Per second billing for serverless GPU capacity?! Infinitely scalable?! Whaaaat

ai engineering is just tweaking config values in a notebook until you run out of runpod credits

I love runpod

Runpod > Sagemaker, VertexAi, AzureML

switching from runpod+cursor to colab made my ml pipeline setup 100x faster, but i'm missing access to claude sonnet 3.7 for interpreting repo files & terminal outputs. need a way to either: 1. connect cursor to colab so the llm sees my terminal outputs 2. efficiently feed colab outputs to an llm without tedious copy/paste what's the best workflow for llm-assisted debugging when your code runs in colab but your preferred assistant lacks context? any MCP servers to give cursor access to colab?

Trained a 7B parameter model in just 90 minutes for $0.80 using LoRA + Runpod. Yes, it’s possible—and no, you don’t need enterprise hardware.

For anyone annoyed with Amazon's (and Azure's and Google's) gatekeeping on their cloud GPU VMs, I recommend @runpod_io None of the 'prove you really need this much power' bs from the majors Just great pricing, availability, and an intuitive UI

Thanks @runpod_io, loving all of the updates! 👀

🏃 Runpod is now available on SkyPilot! ✈️ Get high-end GPUs (3x cheaper) with great availability: sky launch --gpus H100 Great thanks to @runpod_io for contributing this integration to join the Sky!

The @runpod_io event was amazing! One reason we can boast about fast speeds at @jigsawstack is because the cold boot on runpod GPUs is basically nonexistent!

I have been testing work with @runpod_io last 2 weeks and I've to say the service is pretty amazing. Super awesome UX and DevEX (and plenty of GPU backend choices). It's about ~20% pricier than Lambda labs, but worth it IMO given all the harness and workflow they provide that Lambda doesn't. I'm not associated with them in any way or manner, btw. Just a very happy customer.

Why is Huggingface not adding Runpod as a serverless provider? Runpod is 10-15x cheaper for serverless deployment than AWS and GCP

Runpod has great prices as well

Apparently, we got a Kaggle silver medal in the @arcprize for being in position 17th out of 1430 teams 🙃 I wish I had more time to spend on it; we worked on it for a couple of weeks for fun with limited compute (HUGE thanks to @runpod_io!)

I'm proud to be part of the GPU Elite, awarded by @runpod_io 😍

Runpod support > lambdalabs support. For on demand GPUs runpod still works the best ime

thank u runpod i was doing a training run for work when GCP and cloudflare died 🙏🙏 i appreciate u staying online it finished successfully

ai engineering is just tweaking config values in a notebook until you run out of runpod credits

🏃 Runpod is now available on SkyPilot! ✈️ Get high-end GPUs (3x cheaper) with great availability: sky launch --gpus H100 Great thanks to @runpod_io for contributing this integration to join the Sky!

Axolotl works out of the box with @runpod_io's Clusters. It's as easy as running this on each node using the Docker images that we ship.

Introducing SmolLlama! An effort to make a mini-ChatGPT from scratch! Its based on the Llama (123 M) structure I coded and pre-trained on 10B tokens (10k steps) from the FineWeb dataset from scratch using DDP (torchrun) in PyTorch. Used 2xH100 (SXM) 80GB VRAM from Runpod

switching from runpod+cursor to colab made my ml pipeline setup 100x faster, but i'm missing access to claude sonnet 3.7 for interpreting repo files & terminal outputs. need a way to either: 1. connect cursor to colab so the llm sees my terminal outputs 2. efficiently feed colab outputs to an llm without tedious copy/paste what's the best workflow for llm-assisted debugging when your code runs in colab but your preferred assistant lacks context? any MCP servers to give cursor access to colab?

@runpod_io is so goated, first time trying it today and it’s super easy to setup + their ai helper on discord was very helpful If you ever need cpus/gpus I recommend it!

Trained a 7B parameter model in just 90 minutes for $0.80 using LoRA + Runpod. Yes, it’s possible—and no, you don’t need enterprise hardware.

Shoutout to @runpod_io as I work through my first non-trivial machine learning experiment. They have exactly what you need if you're a hobbyist and their prices are about a fifth of the big cloud providers.

i'm a big fan of @runpod_io they're most reliable GPU provider for training and running your models at scale

I love runpod

Needed a GPU for a quick job, didn't want to commit to anything long-term. Runpod was perfect for that. Love that I can just spin one up and shut it down after.

1.3k spent on the training run, this latest release would not have been possible without runpod

Just discovered @runpod_io 🤯🤯🤯 Per second billing for serverless GPU capacity?! Infinitely scalable?! Whaaaat

For anyone annoyed with Amazon's (and Azure's and Google's) gatekeeping on their cloud GPU VMs, I recommend @runpod_io None of the 'prove you really need this much power' bs from the majors Just great pricing, availability, and an intuitive UI

Thanks @runpod_io, loving all of the updates! 👀

Runpod > Sagemaker, VertexAi, AzureML

The @runpod_io event was amazing! One reason we can boast about fast speeds at @jigsawstack is because the cold boot on runpod GPUs is basically nonexistent!

ai engineering is just tweaking config values in a notebook until you run out of runpod credits

I love runpod

Just discovered @runpod_io 🤯🤯🤯 Per second billing for serverless GPU capacity?! Infinitely scalable?! Whaaaat

Runpod support > lambdalabs support. For on demand GPUs runpod still works the best ime

switching from runpod+cursor to colab made my ml pipeline setup 100x faster, but i'm missing access to claude sonnet 3.7 for interpreting repo files & terminal outputs. need a way to either: 1. connect cursor to colab so the llm sees my terminal outputs 2. efficiently feed colab outputs to an llm without tedious copy/paste what's the best workflow for llm-assisted debugging when your code runs in colab but your preferred assistant lacks context? any MCP servers to give cursor access to colab?

Runpod > Sagemaker, VertexAi, AzureML

I'm proud to be part of the GPU Elite, awarded by @runpod_io 😍

i'm a big fan of @runpod_io they're most reliable GPU provider for training and running your models at scale

1.3k spent on the training run, this latest release would not have been possible without runpod

Why is Huggingface not adding Runpod as a serverless provider? Runpod is 10-15x cheaper for serverless deployment than AWS and GCP

I have been testing work with @runpod_io last 2 weeks and I've to say the service is pretty amazing. Super awesome UX and DevEX (and plenty of GPU backend choices). It's about ~20% pricier than Lambda labs, but worth it IMO given all the harness and workflow they provide that Lambda doesn't. I'm not associated with them in any way or manner, btw. Just a very happy customer.

Runpod has great prices as well

Thanks @runpod_io, loving all of the updates! 👀

For anyone annoyed with Amazon's (and Azure's and Google's) gatekeeping on their cloud GPU VMs, I recommend @runpod_io None of the 'prove you really need this much power' bs from the majors Just great pricing, availability, and an intuitive UI

Apparently, we got a Kaggle silver medal in the @arcprize for being in position 17th out of 1430 teams 🙃 I wish I had more time to spend on it; we worked on it for a couple of weeks for fun with limited compute (HUGE thanks to @runpod_io!)

Introducing SmolLlama! An effort to make a mini-ChatGPT from scratch! Its based on the Llama (123 M) structure I coded and pre-trained on 10B tokens (10k steps) from the FineWeb dataset from scratch using DDP (torchrun) in PyTorch. Used 2xH100 (SXM) 80GB VRAM from Runpod

thank u runpod i was doing a training run for work when GCP and cloudflare died 🙏🙏 i appreciate u staying online it finished successfully

🏃 Runpod is now available on SkyPilot! ✈️ Get high-end GPUs (3x cheaper) with great availability: sky launch --gpus H100 Great thanks to @runpod_io for contributing this integration to join the Sky!

Axolotl works out of the box with @runpod_io's Clusters. It's as easy as running this on each node using the Docker images that we ship.

Shoutout to @runpod_io as I work through my first non-trivial machine learning experiment. They have exactly what you need if you're a hobbyist and their prices are about a fifth of the big cloud providers.

The @runpod_io event was amazing! One reason we can boast about fast speeds at @jigsawstack is because the cold boot on runpod GPUs is basically nonexistent!

Trained a 7B parameter model in just 90 minutes for $0.80 using LoRA + Runpod. Yes, it’s possible—and no, you don’t need enterprise hardware.

Needed a GPU for a quick job, didn't want to commit to anything long-term. Runpod was perfect for that. Love that I can just spin one up and shut it down after.

@runpod_io is so goated, first time trying it today and it’s super easy to setup + their ai helper on discord was very helpful If you ever need cpus/gpus I recommend it!