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ariG23498Β 
posted an update 3 months ago
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New post is live!

This time we cover some major updates to transformers.

πŸ€—
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ariG23498Β 
posted an update 5 months ago
cfahlgren1Β 
posted an update 6 months ago
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I ran the Anthropic Misalignment Framework for a few top models and added it to a dataset: cfahlgren1/anthropic-agentic-misalignment-results

You can read the reasoning traces of the models trying to blackmail the user and perform other actions. It's very interesting!!

ariG23498Β 
posted an update 6 months ago
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🚨 Implement KV Cache from scratch in pure PyTorch. 🚨

We have documented all of our learning while implementing KV Cache to nanoVLM. Joint work with @kashif @lusxvr @andito @pcuenq

Blog: hf.co/blog/kv-cache
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cfahlgren1Β 
posted an update 6 months ago
cfahlgren1Β 
posted an update 7 months ago
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Yesterday, we dropped a new conversational viewer for datasets on the hub! πŸ’¬

Actually being able to view and inspect your data is extremely important. This is a big step in making data more accessible and actionable for everyone.

Here's some datasets you can try it out on:
β€’ mlabonne/FineTome-100k
β€’ Salesforce/APIGen-MT-5k
β€’ open-thoughts/OpenThoughts2-1M
β€’ allenai/tulu-3-sft-mixture

Any other good ones?
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cfahlgren1Β 
posted an update 10 months ago
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If you haven't seen yet, we just released Inference Providers πŸ”€

> 4 new serverless inference providers on the Hub 🀯
> Use your HF API key or personal key with all providers πŸ”‘
> Chat with Deepseek R1, V3, and more on HF Hub πŸ‹
> We support Sambanova, TogetherAI, Replicate, and Fal.ai πŸ’ͺ

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.
ariG23498Β 
posted an update 11 months ago
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2852
Tried my hand at simplifying the derivations of Direct Preference Optimization.

I cover how one can reformulate RLHF into DPO. The idea of implicit reward modeling is chef's kiss.

Blog: https://huggingface.co/blog/ariG23498/rlhf-to-dpo
ariG23498Β 
posted an update 11 months ago
cfahlgren1Β 
posted an update 11 months ago
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Wow, I just added Langfuse tracing to the Deepseek Artifacts app and it's really nice πŸ”₯

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 πŸ’ͺ
cfahlgren1Β 
posted an update 11 months ago
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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 πŸ—£οΈ





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cfahlgren1Β 
posted an update 11 months ago
ariG23498Β 
posted an update about 1 year ago
cfahlgren1Β 
posted an update about 1 year ago
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You can just ask things πŸ—£οΈ

"show me messages in the coding category that are in the top 10% of reward model scores"

Download really high quality instructions from the Llama3.1 405B synthetic dataset πŸ”₯

argilla/magpie-ultra-v1.0

cfahlgren1Β 
posted an update about 1 year ago
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We just dropped an LLM inside the SQL Console 🀯

The amazing, new Qwen/Qwen2.5-Coder-32B-Instruct model can now write SQL for any Hugging Face dataset ✨

It's 2025, you shouldn't be hand writing SQL! This is a big step in making it where anyone can do in depth analysis on a dataset. Let us know what you think πŸ€—
cfahlgren1Β 
posted an update about 1 year ago
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observers πŸ”­ - automatically log all OpenAI compatible requests to a datasetπŸ’½

β€’ supports any OpenAI compatible endpoint πŸ’ͺ
β€’ supports DuckDB, Hugging Face Datasets, and Argilla as stores

> pip install observers

No complex framework. Just a few lines of code to start sending your traces somewhere. Let us know what you think! @davidberenstein1957 and I will continue iterating!

Here's an example dataset that was logged to Hugging Face from Ollama: cfahlgren1/llama-3.1-awesome-chatgpt-prompts
cfahlgren1Β 
posted an update about 1 year ago
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You can create charts, leaderboards, and filters on top of any Hugging Face dataset in less than a minute

β€’ ASCII Bar Charts πŸ“Š
β€’ Powered by DuckDB WASM ⚑
β€’ Download results to Parquet πŸ’½
β€’ Embed and Share results with friends πŸ“¬

Do you have any interesting queries?