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

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

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!

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!)

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! 👀

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.

Runpod has great prices as well

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

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?

I love runpod

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

Runpod > Sagemaker, VertexAi, AzureML

@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.

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.

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

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

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

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.

🏃 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

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

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

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 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.

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

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.

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.

Runpod > Sagemaker, VertexAi, AzureML

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 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

Runpod has great prices as well

I love runpod

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

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

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

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

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

🏃 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!

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

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!

Thanks @runpod_io, loving all of the updates! 👀

@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!

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

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.

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

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

I love runpod

@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!

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

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 > Sagemaker, VertexAi, AzureML

Runpod has great prices as well

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

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!

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!)

Thanks @runpod_io, loving all of the updates! 👀

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?

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.

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.

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

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 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!

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

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

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.

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.

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

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

I love runpod

Runpod has great prices as well

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

🏃 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!

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

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

Thanks @runpod_io, loving all of the updates! 👀

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_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!

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!

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!)

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 > Sagemaker, VertexAi, AzureML

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.

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

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?

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