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jklj077  updated a collection about 3 hours ago
QwQ
jklj077  updated a collection about 3 hours ago
QwQ
jklj077  updated a collection about 3 hours ago
QwQ
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Qwen's activity

jklj077 
in Qwen/QwQ-32B about 4 hours ago

是否需要添加系统prompt

1
#23 opened about 5 hours ago by
wphtrying
AdinaY 
posted an update about 5 hours ago
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238
Babel🗼A multilingual LLM supporting 25 languages, released by the Alibaba DAMO team.

Model: Tower-Babel/babel-67c172157372d4d6c4b4c6d5
Paper: Babel: Open Multilingual Large Language Models Serving Over 90% of Global Speakers (2503.00865)

✨ 9B/83B chat & base
✨ Supports 25 languages: English, Chinese, Hindi, Spanish, Arabic, French, Bengali, Portuguese, Russian, Urdu, Indonesian, German, Japanese, Swahili, Filipino, Tamil, Vietnamese, Turkish, Italian, Javanese, Korean, Hausa, Persian, Thai, and Burmese
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littlebird13 
in Qwen/QwQ-32B-Demo about 11 hours ago

Link from model page

#1 opened about 19 hours ago by
victor
littlebird13 
in Qwen/QwQ-32B about 12 hours ago

Add transformers as library!

1
#1 opened about 19 hours ago by
reach-vb
Tonic 
posted an update about 19 hours ago
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413
Powered by KRLabsOrg/lettucedect-large-modernbert-en-v1 from KRLabsOrg.

Detect hallucinations in answers based on context and questions using ModernBERT with 8192-token context support!

### Model Details
- **Model Name**: [lettucedect-large-modernbert-en-v1]( KRLabsOrg/lettucedect-large-modernbert-en-v1)
- **Organization**: [KRLabsOrg](https://huggingface.co/KRLabsOrg)
- **Github**: [https://github.com/KRLabsOrg/LettuceDetect](https://github.com/KRLabsOrg/LettuceDetect)
- **Architecture**: ModernBERT (Large) with extended context support up to 8192 tokens
- **Task**: Token Classification / Hallucination Detection
- **Training Dataset**: [RagTruth]( wandb/RAGTruth-processed)
- **Language**: English
- **Capabilities**: Detects hallucinated spans in answers, provides confidence scores, and calculates average confidence across detected spans.

LettuceDetect excels at processing long documents to determine if an answer aligns with the provided context, making it a powerful tool for ensuring factual accuracy.