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Diaries of Open Source. Part 5!
Diaries of Open Source. Part 5!
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🤯Contextual KTO Mistral PairRM: this model combines iterative KTO, SnorkelAI DPO dataset, Allenai PairRM for ranking, Mistral for the base model, and is a very strong model with Claude 3 quality on AlpacaEval 2.0
🤯Contextual KTO Mistral PairRM: this model combines iterative KTO, SnorkelAI DPO dataset, Allenai PairRM for ranking, Mistral for the base model, and is a very strong model with Claude 3 quality on AlpacaEval 2.0
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Final model: 
Final model: 
resource
https://hf.co/ContextualAI/Contextual_KTO_Mistral_PairRM
model
ContextualAI/Contextual_KTO_Mistral_PairRM
https://hf.co/ContextualAI/Contextual_KTO_Mistral_PairRM
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Dataset: 
Dataset: 
resource
https://hf.co/datasets/snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
dataset
snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
https://hf.co/datasets/snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
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Leaderboard: 
Leaderboard: 
link
https://tatsu-lab.github.io/alpaca_eval/
https://tatsu-lab.github.io/alpaca_eval/
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Base model: 
Base model: 
resource
https://hf.co/mistralai/Mistral-7B-Instruct-v0.2
model
mistralai/Mistral-7B-Instruct-v0.2
https://hf.co/mistralai/Mistral-7B-Instruct-v0.2
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🤏 tinyBenchmarks: Quick and cheap LLM evaluation!
🤏 tinyBenchmarks: Quick and cheap LLM evaluation!
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Code: 
Code: 
link
https://github.com/felipemaiapolo/tinyBenchmarks
https://github.com/felipemaiapolo/tinyBenchmarks
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Paper: 
Paper: 
resource
https://hf.co/papers/2402.14992
paper
2402.14992
https://hf.co/papers/2402.14992
tinyBenchmarks: evaluating LLMs with fewer examples (2402.14992)
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Data: 
Data: 
resource
https://hf.co/datasets/tinyBenchmarks/tinyMMLU
dataset
tinyBenchmarks/tinyMMLU
https://hf.co/datasets/tinyBenchmarks/tinyMMLU
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🎨Transformers.js 2.16 includes StableLM,  speaker verification and diarization, and better chat templating. Try some fun demos!
🎨Transformers.js 2.16 includes StableLM,  speaker verification and diarization, and better chat templating. Try some fun demos!
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- 
- 
resource
https://hf.co/spaces/Xenova/video-object-detection
space
Xenova/video-object-detection
https://hf.co/spaces/Xenova/video-object-detection
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- 
- 
resource
https://hf.co/spaces/Xenova/cross-encoder-web
space
Xenova/cross-encoder-web
https://hf.co/spaces/Xenova/cross-encoder-web
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- 
- 
resource
https://hf.co/spaces/Xenova/the-tokenizer-playground
space
Xenova/the-tokenizer-playground
https://hf.co/spaces/Xenova/the-tokenizer-playground
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🏴‍☠️ Abascus Liberated-Qwen1.5-72B, a Qwen 72B-based model that strongly follows system prompts
🏴‍☠️ Abascus Liberated-Qwen1.5-72B, a Qwen 72B-based model that strongly follows system prompts
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Model: 
Model: 
resource
https://hf.co/abacusai/Liberated-Qwen1.5-72B
model
abacusai/Liberated-Qwen1.5-72B
https://hf.co/abacusai/Liberated-Qwen1.5-72B
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👀Design2Code: benchmark of webpage screenshots  to code
👀Design2Code: benchmark of webpage screenshots  to code
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Data: 
Data: 
resource
https://hf.co/datasets/SALT-NLP/Design2Code
dataset
SALT-NLP/Design2Code
https://hf.co/datasets/SALT-NLP/Design2Code
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Project 
Project 
link
https://salt-nlp.github.io/Design2Code/
https://salt-nlp.github.io/Design2Code/
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Paper 
Paper 
resource
https://hf.co/papers/2403.03163
paper
2403.03163
https://hf.co/papers/2403.03163
Design2Code: How Far Are We From Automating Front-End Engineering? (2403.03163)
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🌎Data and models around the world
🌎Data and models around the world
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- One of the biggest Italian datasets 
- One of the biggest Italian datasets 
link
https://hf.co/datasets/manalog/UsenetArchiveIT
https://hf.co/datasets/manalog/UsenetArchiveIT
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- IndicLLMSuite: argest Pre-training and Instruction Fine-tuning dataset collection across 22 Indic languages 
- IndicLLMSuite: argest Pre-training and Instruction Fine-tuning dataset collection across 22 Indic languages 
resource
https://hf.co/collections/ai4bharat/indicllmsuite-65ee7d225c337fcfa0991707
collection
ai4bharat/indicllmsuite-65ee7d225c337fcfa0991707
https://hf.co/collections/ai4bharat/indicllmsuite-65ee7d225c337fcfa0991707
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- Hebrew-Gemma-11B, the best base Hebrew model 
- Hebrew-Gemma-11B, the best base Hebrew model 
resource
https://huggingface.co/yam-peleg/Hebrew-Gemma-11B
model
yam-peleg/Hebrew-Gemma-11B
https://huggingface.co/yam-peleg/Hebrew-Gemma-11B
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- Komodo-7B, a family of multiple Indonesian languages LLMs 
- Komodo-7B, a family of multiple Indonesian languages LLMs 
resource
https://hf.co/Yellow-AI-NLP/komodo-7b-base
model
Yellow-AI-NLP/komodo-7b-base
https://hf.co/Yellow-AI-NLP/komodo-7b-base
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You can find the previous part at 
You can find the previous part at 
link
https://huggingface.co/posts/osanseviero/127895284909100
https://huggingface.co/posts/osanseviero/127895284909100
Diaries of Open Source. Part 5!

🤯Contextual KTO Mistral PairRM: this model combines iterative KTO, SnorkelAI DPO dataset, Allenai PairRM for ranking, Mistral for the base model, and is a very strong model with Claude 3 quality on AlpacaEval 2.0
Final model: https://hf.co/ContextualAI/Contextual_KTO_Mistral_PairRM
Dataset: https://hf.co/datasets/snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
Leaderboard: https://tatsu-lab.github.io/alpaca_eval/
Base model: https://hf.co/mistralai/Mistral-7B-Instruct-v0.2

🤏 tinyBenchmarks: Quick and cheap LLM evaluation!
Code: https://github.com/felipemaiapolo/tinyBenchmarks
Paper: https://hf.co/papers/2402.14992
Data: https://hf.co/datasets/tinyBenchmarks/tinyMMLU

🎨Transformers.js 2.16 includes StableLM,  speaker verification and diarization, and better chat templating. Try some fun demos!
- https://hf.co/spaces/Xenova/video-object-detection
- https://hf.co/spaces/Xenova/cross-encoder-web
- https://hf.co/spaces/Xenova/the-tokenizer-playground

🏴‍☠️ Abascus Liberated-Qwen1.5-72B, a Qwen 72B-based model that strongly follows system prompts
Model: https://hf.co/abacusai/Liberated-Qwen1.5-72B

👀Design2Code: benchmark of webpage screenshots  to code
Data: https://hf.co/datasets/SALT-NLP/Design2Code
Project https://salt-nlp.github.io/Design2Code/
Paper https://hf.co/papers/2403.03163

🌎Data and models around the world
- One of the biggest Italian datasets https://hf.co/datasets/manalog/UsenetArchiveIT
- IndicLLMSuite: argest Pre-training and Instruction Fine-tuning dataset collection across 22 Indic languages https://hf.co/collections/ai4bharat/indicllmsuite-65ee7d225c337fcfa0991707
- Hebrew-Gemma-11B, the best base Hebrew model https://huggingface.co/yam-peleg/Hebrew-Gemma-11B
- Komodo-7B, a family of multiple Indonesian languages LLMs https://hf.co/Yellow-AI-NLP/komodo-7b-base

You can find the previous part at https://huggingface.co/posts/osanseviero/127895284909100
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