reducto/RolmOCR
Image-Text-to-Text
•
Updated
•
5.69k
•
350
fahrizalfarid
akahana
AI & ML interests
NLP
Recent Activity
liked
a model
5 days ago
reducto/RolmOCR
liked
a dataset
5 days ago
allenai/olmOCR-mix-0225
Organizations
None yet
akahana's activity
liked
a
model
5 days ago
liked
a
dataset
5 days ago
reacted to
severo's
post with 🚀
5 days ago
Post
1851
Need to convert CSV to Parquet?
Use https://www.chatdb.ai/tools/csv-to-parquet-converter. It does the job instantly.
@cfahlgren1 provides many other tools on his website. Approved and bookmarked!
Use https://www.chatdb.ai/tools/csv-to-parquet-converter. It does the job instantly.
@cfahlgren1 provides many other tools on his website. Approved and bookmarked!
- 2 replies
reacted to
luigi12345's
post with 👍
7 days ago
Post
2659
🚀 Meta’s Llama 4 Models Now on Hugging Face!
Meta has released Llama 4 Scout and Llama 4 Maverick, now available on Hugging Face:
• Llama 4 Scout: 17B active parameters, 16-expert Mixture of Experts (MoE) architecture, 10M token context window, fits on a single H100 GPU. 
• Llama 4 Maverick: 17B active parameters, 128-expert MoE architecture, 1M token context window, optimized for DGX H100 systems. 
🔥 Key Features:
• Native Multimodality: Seamlessly processes text and images. 
• Extended Context Window: Up to 10 million tokens for handling extensive inputs.
• Multilingual Support: Trained on 200 languages, with fine-tuning support for 12, including Arabic, Spanish, and German. 
🛠️ Access and Integration:
• Model Checkpoints: Available under the meta-llama organization on the Hugging Face Hub.
• Transformers Compatibility: Fully supported in transformers v4.51.0 for easy loading and fine-tuning.
• Efficient Deployment: Supports tensor-parallelism and automatic device mapping.
These models offer developers enhanced capabilities for building sophisticated, multimodal AI applications. 
Meta has released Llama 4 Scout and Llama 4 Maverick, now available on Hugging Face:
• Llama 4 Scout: 17B active parameters, 16-expert Mixture of Experts (MoE) architecture, 10M token context window, fits on a single H100 GPU. 
• Llama 4 Maverick: 17B active parameters, 128-expert MoE architecture, 1M token context window, optimized for DGX H100 systems. 
🔥 Key Features:
• Native Multimodality: Seamlessly processes text and images. 
• Extended Context Window: Up to 10 million tokens for handling extensive inputs.
• Multilingual Support: Trained on 200 languages, with fine-tuning support for 12, including Arabic, Spanish, and German. 
🛠️ Access and Integration:
• Model Checkpoints: Available under the meta-llama organization on the Hugging Face Hub.
• Transformers Compatibility: Fully supported in transformers v4.51.0 for easy loading and fine-tuning.
• Efficient Deployment: Supports tensor-parallelism and automatic device mapping.
These models offer developers enhanced capabilities for building sophisticated, multimodal AI applications. 
liked
a
dataset
10 days ago
liked
2
datasets
21 days ago
updated
a
dataset
26 days ago
published
a
dataset
26 days ago
updated
a
dataset
28 days ago
updated
a
dataset
about 1 month ago
published
2
datasets
about 1 month ago
updated
a
model
about 1 month ago
updated
a
dataset
about 1 month ago
reacted to
lewtun's
post with 🔥
about 1 month ago
Post
2344
Introducing OlympicCoder: a series of open reasoning models that can solve olympiad-level programming problems 🧑💻
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger 💪
Together with the models, we are releasing:
📊CodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
🏆 IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 7B open-r1/OlympicCoder-7B
- 32B open-r1/OlympicCoder-32B
We find that OlympicCoder models outperform Claude 3.7 Sonnet, as well as others over 100x larger 💪
Together with the models, we are releasing:
📊CodeForces-CoTs: new dataset of code problems from the most popular competitive coding platform, with R1 traces in C++ and Python open-r1/codeforces-cots
🏆 IOI'2024: a new benchmark of VERY hard programming problems where even frontier models struggle to match human performance open-r1/ioi
For links to the models and datasets, check out our latest progress report from Open R1: https://huggingface.co/blog/open-r1/update-3
- 1 reply
reacted to
prithivMLmods's
post with 🤗
about 1 month ago
Post
2797
Variable Demo for Two Image-to-Text-to-Text Multimodals 🌠
📜Space: prithivMLmods/Multimodal-OCR
By default, it will use:
prithivMLmods/Qwen2-VL-OCR-2B-Instruct or
prithivMLmods/Qwen2-VL-OCR2-2B-Instruct
To trigger Aya-Vision's 8B by @aya-vision , use the prompt:
https://huggingface.co/CohereForAI/aya-vision-8b
📜Space: prithivMLmods/Multimodal-OCR
By default, it will use:
prithivMLmods/Qwen2-VL-OCR-2B-Instruct or
prithivMLmods/Qwen2-VL-OCR2-2B-Instruct
To trigger Aya-Vision's 8B by @aya-vision , use the prompt:
https://huggingface.co/CohereForAI/aya-vision-8b
updated
2
models
about 1 month ago