SFR-Embedding Model
SFR-Embedding-Mistral 显著提升文本嵌入模型，构建在 E5-mistral-7b-instruct 和 Mistral-7B-v0.1 的坚实基础之上。
TextSynth
SFR-Embedding Model
| Launched | |
| Pricing Model | Free |
| Starting Price | |
| Tech used | |
| Tag | Text Analysis,Data Analysis |
TextSynth
| Launched | 2019-05 |
| Pricing Model | Free Trial |
| Starting Price | |
| Tech used | Apache |
| Tag | Data Analysis,Content Creation |
SFR-Embedding Model Rank/Visit
| Global Rank | |
| Country | |
| Month Visit |
Top 5 Countries
Traffic Sources
TextSynth Rank/Visit
| Global Rank | 2557702 |
| Country | United States |
| Month Visit | 7462 |
Top 5 Countries
48.91%
16.82%
11.15%
10.12%
7.3%
United States
India
Germany
Italy
Brazil
Traffic Sources
7.91%
1.02%
0.09%
8.92%
38.52%
43.28%
social
paidReferrals
mail
referrals
search
direct
Estimated traffic data from Similarweb
What are some alternatives?
When comparing SFR-Embedding Model and TextSynth, you can also consider the following products
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Embaas - embaas 提供诸如内嵌生成、文档文本提取、文档至 emb 等强大功能
FastEmbed - FastEmbed 是一款轻量、高速的 Python 库，专注于高性能地生成文本嵌入。我们已支持众多主流文本模型。如果您有新的模型需求，欢迎随时在 Github 上提交 issue，我们将积极评估并考虑加入。
Mistral OCR - 利用 Mistral OCR 解锁文档数据！快速、精准的 API 提取文本、表格、公式等内容，并提供多语言支持。
Mistral Large - Mistral Large 是我们的旗舰模型，具备顶尖的推理能力。此外，它还可在 Azure 上使用。