Tokenizer Choice For LLM Training: Negligible or Crucial?
Paper
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2310.08754
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Published
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2
OSCAR
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malteos
authored
10
papers
3 days ago
Towards an Open Platform for Legal Information
Paper
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2005.13342
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Published
Aspect-based Document Similarity for Research Papers
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2010.06395
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Published
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings
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2202.06671
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Published
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2
Specialized Document Embeddings for Aspect-based Similarity of Research Papers
Paper
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2203.14541
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Published
Investigating Gender Bias in Turkish Language Models
Paper
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2404.11726
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Published
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1
Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning
Paper
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2301.09626
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Published
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2
Progress Report: Towards European LLMs
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2410.03730
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Published
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2
Data Processing for the OpenGPT-X Model Family
Paper
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2410.08800
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Published
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1
MMTEB: Massive Multilingual Text Embedding Benchmark
Paper
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2502.13595
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Published
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28
albertvillanova
posted
an
update
20 days ago
Post
3440
🚀 Introducing
@huggingface
Open Deep-Research💥
In just 24 hours, we built an open-source agent that:
✅ Autonomously browse the web
✅ Search, scroll & extract info
✅ Download & manipulate files
✅ Run calculations on data
55% on GAIA validation set! Help us improve it!💡
https://huggingface.co/blog/open-deep-research
In just 24 hours, we built an open-source agent that:
✅ Autonomously browse the web
✅ Search, scroll & extract info
✅ Download & manipulate files
✅ Run calculations on data
55% on GAIA validation set! Help us improve it!💡
https://huggingface.co/blog/open-deep-research
- 3 replies
[bot] Conversion to Parquet
#1 opened 8 months ago
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"text" feature is Value(dtype='string', id=None)
#3 opened 6 months ago
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homersimpson
albertvillanova
posted
an
update
about 2 months ago
Post
2073
Discover all the improvements in the new version of Lighteval: https://huggingface.co/docs/lighteval/
mbrack
authored
a
paper
2 months ago
matthieufp
updated
a
dataset
3 months ago
albertvillanova
posted
an
update
3 months ago
Post
1792
🚨 How green is your model? 🌱 Introducing a new feature in the Comparator tool: Environmental Impact for responsible #LLM research!
👉 open-llm-leaderboard/comparator
Now, you can not only compare models by performance, but also by their environmental footprint!
🌍 The Comparator calculates CO₂ emissions during evaluation and shows key model characteristics: evaluation score, number of parameters, architecture, precision, type... 🛠️
Make informed decisions about your model's impact on the planet and join the movement towards greener AI!
👉 open-llm-leaderboard/comparator
Now, you can not only compare models by performance, but also by their environmental footprint!
🌍 The Comparator calculates CO₂ emissions during evaluation and shows key model characteristics: evaluation score, number of parameters, architecture, precision, type... 🛠️
Make informed decisions about your model's impact on the planet and join the movement towards greener AI!
sagot
authored
a
paper
3 months ago
mbrack
updated
a
dataset
3 months ago
albertvillanova
posted
an
update
4 months ago
Post
1592
🚀 New feature of the Comparator of the 🤗 Open LLM Leaderboard: now compare models with their base versions & derivatives (finetunes, adapters, etc.). Perfect for tracking how adjustments affect performance & seeing innovations in action. Dive deeper into the leaderboard!
🛠️ Here's how to use it:
1. Select your model from the leaderboard.
2. Load its model tree.
3. Choose any base & derived models (adapters, finetunes, merges, quantizations) for comparison.
4. Press Load.
See side-by-side performance metrics instantly!
Ready to dive in? 🏆 Try the 🤗 Open LLM Leaderboard Comparator now! See how models stack up against their base versions and derivatives to understand fine-tuning and other adjustments. Easier model analysis for better insights! Check it out here: open-llm-leaderboard/comparator 🌐
🛠️ Here's how to use it:
1. Select your model from the leaderboard.
2. Load its model tree.
3. Choose any base & derived models (adapters, finetunes, merges, quantizations) for comparison.
4. Press Load.
See side-by-side performance metrics instantly!
Ready to dive in? 🏆 Try the 🤗 Open LLM Leaderboard Comparator now! See how models stack up against their base versions and derivatives to understand fine-tuning and other adjustments. Easier model analysis for better insights! Check it out here: open-llm-leaderboard/comparator 🌐