Qwen2-11.3B
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Explore AI models 84995
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View details ↗eliza-1
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View details ↗jiwo-0.8b
eljiwo基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗cryptobert
ElKulakoFor academic reference, cite the following paper: https://ieeexplore.ieee.org/document/10223689 CryptoBERT is a pre-trained NLP model to analyse the language and sentiments of cryptocurrency-related social media posts and messages. It was built by further training the vinai's bertweet-base language model on the cryptocurrency domain, using a corpus of over 3.2M unique cryptocurrency-related social media posts. (A research paper with more details will follow soon.) The model was trained on the following labels: "Bearish" : 0, "Neutral": 1, "Bullish": 2 CryptoBERT's sentiment classification head was fine-tuned on a balanced dataset of 2M labelled StockTwits posts, sampled from ElKulako/stocktwits-crypto.
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View details ↗propella-1-0.6b
ellamindpropella-1 is a family of small multilingual LLMs that annotate text documents across six categories: core content, classification, quality & value, audience & purpose, safety & compliance, and geographic relevance. The annotations can be used to filter, select, and curate LLM training data at scale. *Disclaimer: This is a research project, not an official ellamind product. For production-ready evaluation solutions, check out elluminate.* propella-1 models evaluate documents across 18 properties organized into six categories: | Category | Property | Short Description | |----------|----------|-------------| | **Core Content** | Content Integrity | Completeness and technical quality of the content | | | Content Ratio | Proportion of content vs. navigation/UI elements | | | Content Length | Amount of substantive content | | **Classification** | One-Sentence Description | Ultra-short neutral description of the document | | | Content Type | Functional structure and purpose | | | Business Sector | Industry domain relevance | | | Technical Content | Type and intensity of specialized knowledge | | **Quality & Value** | Content Quality | Overall writing and presentation quality | | | Information Density | Ratio of valuable information to redundancy | | | Educational Value | Potential for teaching and learning | | | Reasoning Indicators | Presence of logical reasoning and analysis | | **Audience & Purpose** | Audience Level | Target sophistication level | | | Commercial Bias | Commercial influence on objectivity | | | Time-Sensitivity | How content value changes over time | | **Safety & Compliance** | Content Safety | Presence of inappropriate or harmful content | | | PII Presence | Contains personally identifiable information | | **Geographic** | Regional Relevance | Primary regional/cultural context | | | Country Relevance | Specific country relevance |
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View details ↗propella-1-4b
ellamindpropella-1 is a family of small multilingual LLMs that annotate text documents across six categories: core content, classification, quality & value, audience & purpose, safety & compliance, and geographic relevance. The annotations can be used to filter, select, and curate LLM training data at scale. *Disclaimer: This is a research project, not an official ellamind product. For production-ready evaluation solutions, check out elluminate.* propella-1 models evaluate documents across 18 properties organized into six categories: | Category | Property | Short Description | |----------|----------|-------------| | **Core Content** | Content Integrity | Completeness and technical quality of the content | | | Content Ratio | Proportion of content vs. navigation/UI elements | | | Content Length | Amount of substantive content | | **Classification** | One-Sentence Description | Ultra-short neutral description of the document | | | Content Type | Functional structure and purpose | | | Business Sector | Industry domain relevance | | | Technical Content | Type and intensity of specialized knowledge | | **Quality & Value** | Content Quality | Overall writing and presentation quality | | | Information Density | Ratio of valuable information to redundancy | | | Educational Value | Potential for teaching and learning | | | Reasoning Indicators | Presence of logical reasoning and analysis | | **Audience & Purpose** | Audience Level | Target sophistication level | | | Commercial Bias | Commercial influence on objectivity | | | Time-Sensitivity | How content value changes over time | | **Safety & Compliance** | Content Safety | Presence of inappropriate or harmful content | | | PII Presence | Contains personally identifiable information | | **Geographic** | Regional Relevance | Primary regional/cultural context | | | Country Relevance | Specific country relevance |
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View details ↗sui-1-24b-fp8
ellamind基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Klein9B_Checkpoints
EllaPriest45基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Krea2_Checkpoints
EllaPriest45基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗LTX2.5_base
EllaPriest45基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗MinimaxH3_base
EllaPriest45基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Ornith-1.0_CodingAgent
EllaPriest45基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Qwen3.8_27B
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View details ↗Wan2.2_Checkpoints
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View details ↗Qwen2.5-Math-7B-16k-think
Elliott基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗No matching models
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