cfahlgren1 (Caleb Fahlgren)

replied to severo's post 5 days ago

Awesome! How did you find it? SEO?

It's been a long while since i've updated anything there, so hopefully most things continue to work 🤣🤞. My journey to HF came from there though from what feels like long ago https://x.com/calebfahlgren/status/1785827324283281572

replied to OFT's post 11 days ago

It depends on the compute time on the GPU which would show why some calls may be more expensive than others. For example, Flux will be more expensive if it takes longer than another request.

Source: https://huggingface.co/docs/inference-providers/en/pricing#hf-inference-cost

reacted to OFT's post with 👀 12 days ago

Post

1885

HF's new system makes me feel like they are not transparent on their pricing and making me feel they are not trustworthy.

6 replies

·

replied to OFT's post 12 days ago

Curious what is making it confusing?

reacted to onekq's post with 🚀 27 days ago

Post

2295

Introducing 🎉 OneSQL-v0.1🥳, our first text-to-SQL model based on Qwen2.5-Coder. This model has achieved an EX score of 63.33 on the BIRD leaderboard (https://bird-bench.github.io/).

The model family includes 7B and 32B,
onekq-ai/onesql-v01-qwen-67d8e3eb1611c5532bb90c5f
and can be also found on Ollama (https://ollama.com/onekq/OneSQL-v0.1-Qwen)

My goal is to make OneSQL the most usable open-weights model for text-to-SQL. I'm currently working on best practices to help users use this model the right away and avoid pitfalls. After that, I plan to train the next version to push for a higher EX score.

Enjoy this model and feel free to share comments/questions 🤗

1 reply

·

reacted to jasoncorkill's post with 👍 about 2 months ago

Post

2856

Integrating human feedback is vital for evolving AI models. Boost quality, scalability, and cost-effectiveness with our crowdsourcing tool!

..Or run A/B tests and gather thousands of responses in minutes. Upload two images, ask a question, and watch the insights roll in!

Check it out here and let us know your feedback: https://app.rapidata.ai/compare

reacted to vikhyatk's post with 🔥 about 2 months ago

Post

3104

🚨 New VQA + captioning dataset! moondream/megalith-mdqa

Images from Megalith, captioned using Moondream, then transformed to short-form QA.

9M+ images, 6-10 QA pairs per image.

posted an update 3 months ago

Post

2171

If you haven't seen yet, we just released Inference Providers 🔀

> 4 new serverless inference providers on the Hub 🤯
> Use your HF API key or personal key with all providers 🔑
> Chat with Deepseek R1, V3, and more on HF Hub 🐋
> We support Sambanova, TogetherAI, Replicate, and Fal.ai 💪

Best of all, we don't charge any markup on top of the provider 🫰 Have you tried it out yet? HF Pro accounts get $2 of free usage for the provider inference.

replied to their post 3 months ago

Hey @Sayan01

If you click Save Query then you'll see Download as an option in the menu

reacted to hexgrad's post with 🔥 3 months ago

Post

20332

📣 Looking for labeled, high-quality synthetic audio/TTS data 📣 Have you been or are you currently calling API endpoints from OpenAI, ElevenLabs, etc? Do you have labeled audio data sitting around gathering dust? Let's talk! Join https://discord.gg/QuGxSWBfQy or comment down below.

If your data exceeds quantity & quality thresholds and is approved into the next hexgrad/Kokoro-82M training mix, and you permissively DM me the data under an effective Apache license, then I will DM back the corresponding voicepacks for YOUR data if/when the next Apache-licensed Kokoro base model drops.

What does this mean? If you've been calling closed-source TTS or audio API endpoints to:
- Build voice agents
- Make long-form audio, like audiobooks or podcasts
- Handle customer support, etc
Then YOU can contribute to the training mix and get useful artifacts in return. ❤️

More details at hexgrad/Kokoro-82M#21

21 replies

·

reacted to merve's post with ❤️ 3 months ago

Post

3681

What a beginning to this year in open ML 🤠
Let's unwrap! merve/jan-10-releases-677fe34177759de0edfc9714

Multimodal 🖼️
> ByteDance released SA2VA: a family of vision LMs that can take image, video, text and visual prompts
> moondream2 is out with new capabilities like outputting structured data and gaze detection!
> Dataset: Alibaba DAMO lab released multimodal textbook — 22k hours worth of samples from instruction videos 🤯
> Dataset: SciCap captioning on scientific documents benchmark dataset is released along with the challenge!

LLMs 💬
> Microsoft released Phi-4, sota open-source 14B language model 🔥
> Dolphin is back with Dolphin 3.0 Llama 3.1 8B 🐬🐬
> Prime-RL released Eurus-2-7B-PRIME a new language model trained using PRIME alignment
> SmallThinker-3B is a new small reasoning LM based on Owen2.5-3B-Instruct 💭
> Dataset: QWQ-LONGCOT-500K is the dataset used to train SmallThinker, generated using QwQ-32B-preview 📕
> Dataset: @cfahlgren1 released React Code Instructions: a dataset of code instruction-code pairs 📕
> Dataset: Qwen team is on the roll, they just released CodeElo, a dataset of code preferences 👩🏻‍💻

Embeddings 🔖
> @MoritzLaurer released zero-shot version of ModernBERT large 👏
> KaLM is a new family of performant multilingual embedding models with MIT license built using Qwen2-0.5B

Image/Video Generation ⏯️
> NVIDIA released Cosmos, a new family of diffusion/autoregressive World Foundation Models generating worlds from images, videos and texts 🔥
> Adobe released TransPixar: a new text-to-video model that can generate assets with transparent backgrounds (a first!)
> Dataset: fal released cosmos-openvid-1m Cosmos-tokenized OpenVid-1M with samples from OpenVid-1M

Others
> Prior Labs released TabPFNv2, the best tabular transformer is out for classification and regression
> Metagene-1 is a new RNA language model that can be used for pathogen detection, zero-shot embedding and genome understanding

posted an update 3 months ago

Post

1767

Wow, I just added Langfuse tracing to the Deepseek Artifacts app and it's really nice 🔥

It allows me to visualize and track more things along with the cfahlgren1/react-code-instructions dataset.

It was just added as a one click Docker Space template, so it's super easy to self host 💪

posted an update 3 months ago

Post

2257

You'll notice the AI in the SQL Console is much better at working with chatml conversations:

Here's example of unnesting the cfahlgren1/react-code-instructions in less than 10 seconds by asking it. Check it out here: cfahlgren1/react-code-instructions

- "show me the average assistant response length"
- "extract user, system, and assistant messages into separate columns"

It's super easy to work with conversational datasets now with natural language 🗣️

2 replies

·

reacted to clem's post with 🚀🤗❤️ 3 months ago

Post

4383

Cool to see @ylecun joining the top 10 of most followed on HF!

(and leaderboard by @mvaloatto is here: mvaloatto/TCTF)

2 replies

·

posted an update 3 months ago

Post

3342

The deepseek-ai/DeepSeek-V3 is very good! I have been playing with it and found it is really good at one-shotting a pretty good landing page.

You can play with it here: https://deepseek-artifacts.vercel.app

All the responses get saved in the cfahlgren1/react-code-instructions dataset. Hopefully we can build one of the biggest, highest quality frontend datasets on the hub 💪

reacted to davidberenstein1957's post with 🧠👀 3 months ago

Post

2048

Fine-tuning ModernBERT for text classification using synthetic data generation

From prompt to model in 3 steps.
1 dataset description
20 minutes of generating
60 minutes of fine-tuning on my Macbook Pro

Tutorial: https://nbsanity.com/static/552eb50cbd91bedb4e5b73fddca2664a/fine-tune-modernbert-classifier.html

reacted to lorraine2's post with 🚀 4 months ago

Post

2009

🦙New NVIDIA paper: LLaMA-Mesh 🦙

We enable large language models to generate and understand 3D meshes by representing them as text and fine-tuning. This unifies the 3D and text modalities in a single model and preserves language abilities, unlocking conversational 3D creation with mesh understanding.

🔎 Project Page: https://research.nvidia.com/labs/toronto-ai/LLaMA-Mesh/
🕹️ Interactive Demo: Zhengyi/LLaMA-Mesh (courtesy of HuggingFace and Gradio)
📖 Full Paper: https://arxiv.org/abs/2411.09595
👨‍💻Code: https://github.com/nv-tlabs/LLaMa-Mesh
💾 Model Checkpoint: Zhengyi/LLaMA-Mesh
🧩 Blender Addon: https://github.com/huggingface/meshgen (courtesy of Dylan Ebert)
🎥 5-min Overview Video: https://youtu.be/eZNazN-1lPo?si=-idQa5aaceVw0Bbj (courtesy of AI Papers Academy)

Caleb Fahlgren PRO

AI & ML interests

Recent Activity

Organizations

cfahlgren1's activity