Argilla 2.4: Easily Build Fine-Tuning and Evaluation datasets on the Hub β No Code Required
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Daniel Vila
dvilasuero
AI & ML interests
RLHF, RLAIF, DPO, data, data, data
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liked
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mlabonne/orca-agentinstruct-1M-v1-cleaned
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open-acc/README
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Post
946
@Jesse-marqo
and the Marqo team are killing it on the Hub: top embedding models and datasets!
Here's how to start using their new evaluation dataset for curation and labelling:
1. Deploy Argilla on Spaces: https://huggingface.co/new-space?template=argilla%2Fargilla-template-space
2. Load Marqo/amazon-products-eval with the UI wizard.
3. Start curating!
Here's how to start using their new evaluation dataset for curation and labelling:
1. Deploy Argilla on Spaces: https://huggingface.co/new-space?template=argilla%2Fargilla-template-space
2. Load Marqo/amazon-products-eval with the UI wizard.
3. Start curating!
Post
633
Build datasets for AI on the Hugging Face Hubβ10x easier than ever!
Today, I'm excited to share our biggest feature since we joined Hugging Face.
Hereβs how it works:
1. Pick a datasetβupload your own or choose from 240K open datasets.
2. Paste the Hub dataset ID into Argilla and set up your labeling interface.
3. Share the URL with your team or the whole community!
And the best part? Itβs:
- No code β no Python needed
- Integrated β all within the Hub
- Scalable β from solo labeling to 100s of contributors
I am incredibly proud of the team for shipping this after weeks of work and many quick iterations.
Let's make this sentence obsolete: "Everyone wants to do the model work, not the data work."
Read, share, and like the HF blog post:
https://huggingface.co/blog/argilla-ui-hub
Today, I'm excited to share our biggest feature since we joined Hugging Face.
Hereβs how it works:
1. Pick a datasetβupload your own or choose from 240K open datasets.
2. Paste the Hub dataset ID into Argilla and set up your labeling interface.
3. Share the URL with your team or the whole community!
And the best part? Itβs:
- No code β no Python needed
- Integrated β all within the Hub
- Scalable β from solo labeling to 100s of contributors
I am incredibly proud of the team for shipping this after weeks of work and many quick iterations.
Let's make this sentence obsolete: "Everyone wants to do the model work, not the data work."
Read, share, and like the HF blog post:
https://huggingface.co/blog/argilla-ui-hub
Papers
1
spaces
40
models
33
dvilasuero/DistilabelOpenHermes-2.5-mistral-7b-mix2
Text Generation
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dvilasuero/Distilabel-OpenHermes-2.5-Mistral-7B-v2
Text Generation
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dvilasuero/Capystral-Mistral-7B-Instruct
Text Generation
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dvilasuero/CapMistral-7B-Instruct-1epoch
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dvilasuero/CapMistral-7B-Instruct
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dvilasuero/Distilabel-Nous-Capybara-7B-V1.9
Text Generation
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dvilasuero/DistilabeledHermes-2.5-Mistral-7B
Text Generation
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dvilasuero/phi2-lora-quantized-distilabel-intel-orca-dpo-pairs
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dvilasuero/DistilabelBeagle14-7B
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dvilasuero/distilabeled-Magicoder-S-DS-6.7B
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datasets
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dvilasuero/code_contests_qwen_coder
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dvilasuero/img_prefs_style_full
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dvilasuero/img_prefs_style
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dvilasuero/stylish_image_preferences_v3
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dvilasuero/stylish_image_preferences_v2
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dvilasuero/stylish_image_preferences
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dvilasuero/imgeval
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dvilasuero/optional-field
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dvilasuero/sentiment-csv
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dvilasuero/meta-llama_Llama-3.1-70B-Instruct_cot_ifeval_20241017_134405
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