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tom

roseking

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maching learning

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posted an update 3 days ago

🎉 Update: HF Downloader now supports English! 🌏 We're excited to announce that HF Downloader now fully supports English interface! ✨ What's New: - Complete English UI - Bilingual documentation - Seamless language switching - Real-time translation of download status 🔍 Whether you're downloading: - Models - Datasets - Spaces The interface will adapt to your language preference automatically. 🚀 Try it now: Switch languages easily in the top-right corner of the app! #HuggingFace #OpenSource #Update #GUI

replied to their post 3 days ago

🤗 Hugging Face Download Tool The Hugging Face Download Tool is a sophisticated graphical user interface application designed to simplify the process of downloading resources from Hugging Face repositories. This tool addresses common challenges in model and file downloads through its intelligent features and user-friendly interface. ✨ Key Features - 🖥️ Intuitive graphical interface for easy operation - 🔄 Advanced retry mechanism with smart error handling - ⏸️ Resume capability for interrupted downloads - 📊 Real-time download status monitoring - 🔐 Secure access to private repositories via token authentication 🛠️ Technical Highlights The tool implements several advanced features to ensure reliable downloads: - 📦 Chunk-based downloading with 1MB segments - ⚡ Adaptive retry intervals (5-300 seconds) based on error types - 🔌 Connection pooling for optimized performance - 🛡️ Built-in rate limiting protection - 🔑 Secure token handling for private repository access This tool is ideal for researchers, developers, and AI practitioners who regularly work with Hugging Face resources and need a reliable, user-friendly download solution. 💻 It supports all major operating systems and requires minimal setup, making it accessible to users of all technical levels. 🚀 GitHub：https://github.com/2404589803/hf_downloader

reacted to their post with 😎 4 days ago

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posted an update 3 days ago

Post

2422

🎉 Update: HF Downloader now supports English!

🌏 We're excited to announce that HF Downloader now fully supports English interface!

✨ What's New:
- Complete English UI
- Bilingual documentation
- Seamless language switching
- Real-time translation of download status

🔍 Whether you're downloading:
- Models
- Datasets
- Spaces

The interface will adapt to your language preference automatically.

🚀 Try it now: Switch languages easily in the top-right corner of the app!

#HuggingFace #OpenSource #Update #GUI

replied to their post 3 days ago

reacted to their post with 😎 4 days ago

Post

2583

🤗 Hugging Face Download Tool

The Hugging Face Download Tool is a sophisticated graphical user interface application designed to simplify the process of downloading resources from Hugging Face repositories. This tool addresses common challenges in model and file downloads through its intelligent features and user-friendly interface.

✨ Key Features
- 🖥️ Intuitive graphical interface for easy operation
- 🔄 Advanced retry mechanism with smart error handling
- ⏸️ Resume capability for interrupted downloads
- 📊 Real-time download status monitoring
- 🔐 Secure access to private repositories via token authentication

🛠️ Technical Highlights
The tool implements several advanced features to ensure reliable downloads:
- 📦 Chunk-based downloading with 1MB segments
- ⚡ Adaptive retry intervals (5-300 seconds) based on error types
- 🔌 Connection pooling for optimized performance
- 🛡️ Built-in rate limiting protection
- 🔑 Secure token handling for private repository access

This tool is ideal for researchers, developers, and AI practitioners who regularly work with Hugging Face resources and need a reliable, user-friendly download solution. 💻 It supports all major operating systems and requires minimal setup, making it accessible to users of all technical levels. 🚀

GitHub：https://github.com/2404589803/hf_downloader

3 replies

posted an update 6 days ago

Post

2583

🤗 Hugging Face Download Tool

The Hugging Face Download Tool is a sophisticated graphical user interface application designed to simplify the process of downloading resources from Hugging Face repositories. This tool addresses common challenges in model and file downloads through its intelligent features and user-friendly interface.

✨ Key Features
- 🖥️ Intuitive graphical interface for easy operation
- 🔄 Advanced retry mechanism with smart error handling
- ⏸️ Resume capability for interrupted downloads
- 📊 Real-time download status monitoring
- 🔐 Secure access to private repositories via token authentication

🛠️ Technical Highlights
The tool implements several advanced features to ensure reliable downloads:
- 📦 Chunk-based downloading with 1MB segments
- ⚡ Adaptive retry intervals (5-300 seconds) based on error types
- 🔌 Connection pooling for optimized performance
- 🛡️ Built-in rate limiting protection
- 🔑 Secure token handling for private repository access

This tool is ideal for researchers, developers, and AI practitioners who regularly work with Hugging Face resources and need a reliable, user-friendly download solution. 💻 It supports all major operating systems and requires minimal setup, making it accessible to users of all technical levels. 🚀

GitHub：https://github.com/2404589803/hf_downloader

3 replies

New activity in roseking/xiaohongshu-train_data 5 months ago

When will you have more xiaohongshu data?

#2 opened 7 months ago by

Elizabeth819

reacted to their post with 🤝 7 months ago

Post

1145

hf-daily-paper-newsletter-chinese，Using glm-4 agents, interpret hugging face's daily papers in simplified Chinese

https://github.com/2404589803/hf-daily-paper-newsletter-chinese

posted an update 7 months ago

Post

1145

hf-daily-paper-newsletter-chinese，Using glm-4 agents, interpret hugging face's daily papers in simplified Chinese

https://github.com/2404589803/hf-daily-paper-newsletter-chinese

liked 3 datasets 11 months ago

reacted to julien-c's post with ❤️ 11 months ago

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Finally found my go-to hat for 2024 😎

Thanks to https://huggingface.co/fal-ai

8 replies

reacted to julien-c's post with 👍🤝 12 months ago

Post

Finally found my go-to hat for 2024 😎

Thanks to https://huggingface.co/fal-ai

8 replies

liked a dataset 12 months ago

roseking/xiaohongshu-train_data

Viewer • Updated Jan 21, 2024 • 52 • 35 • 1

updated a dataset 12 months ago

roseking/xiaohongshu-train_data

Viewer • Updated Jan 21, 2024 • 52 • 35 • 1

upvoted a collection 12 months ago

Daily Papers

Collection

1 item • Updated Oct 26, 2023 • 65

reacted to akhaliq's post with 👍 12 months ago

Post

Self-Rewarding Language Models

paper page: Self-Rewarding Language Models (2401.10020)

Fine-tuning Llama 2 70B on three iterations of our approach yields a model that outperforms many existing systems on the AlpacaEval 2.0 leaderboard, including Claude 2, Gemini Pro, and GPT-4 0613

1 reply

reacted to gsarti's post with 👍 12 months ago

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🔍 Today's pick in Interpretability & Analysis of LMs: Can Large Language Models Explain Themselves? by @andreasmadsen Sarath Chandar & @sivareddyg

LLMs can provide wrong but convincing explanations for their behavior, and this might lead to ill-placed confidence in their predictions. This study uses self-consistency checks to measure the faithfulness of LLM explanations: if an LLM says a set of words is important for making a prediction, then it should not be able to make the same prediction without these words. Results demonstrate that LLM self-explanations faithfulness of self-explanations cannot be reliably trusted, as they prove to be very task and model dependent, with bigger model generally producing more faithful explanations.

📄 Paper: Can Large Language Models Explain Themselves? (2401.07927)

1 reply

reacted to Linaqruf's post with ❤️ 12 months ago

Post

First post!
Very cool feature.

4 replies

reacted to dhuynh95's post with 👍 12 months ago

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🪟32k-context BERT for embedding and RAG on long corpus

Monarch Mixer is a new architecture to enable long context BERT for large corpus and can be fine-tuned for large context retrieval.

Quite interesting and important as BERT is still the most used LLM in production for "old school" tasks like classification, NER, embeddings, but is also a key component for RAG.

Paper: https://arxiv.org/abs/2310.12109
Blog: https://hazyresearch.stanford.edu/blog/2024-01-11-m2-bert-retrieval
GitHub: https://github.com/HazyResearch/m2

1 reply