Cohere's Embed Models (Details and Application)
Embed models can be used to generate embeddings from text or classify it based on various parameters. Embeddings can be used for estimating semantic similarity between two texts, choosing a sentence which is most likely to follow another sentence, or categorizing user feedback. When used with the Classify endpoint, embeddings can be used for any classification or analysis task.
| Latest Model | Description | Modality | Dimensions | Max Tokens (Context Length) | Similarity Metric | Endpoints |
|---|---|---|---|---|---|---|
embed-v4.0 |
A model that allows for text and images to be classified or turned into embeddings | Text, Images, Mixed texts/images (i.e. PDFs) | One of '[256, 512, 1024, 1536 (default)]' | 128k | Cosine Similarity, Dot Product Similarity, Euclidean Distance | Embed |
embed-english-v3.0 |
A model that allows for text to be classified or turned into embeddings. English only. | Text, Images | 1024 | 512 | Cosine Similarity, Dot Product Similarity, Euclidean Distance | Embed, Embed Jobs |
embed-english-light-v3.0 |
A smaller, faster version of embed-english-v3.0. Almost as capable, but a lot faster. English only. |
Text, Images | 384 | 512 | Cosine Similarity, Dot Product Similarity, Euclidean Distance | Embed, Embed Jobs |
embed-multilingual-v3.0 |
Provides multilingual classification and embedding support. See supported languages here. | Text, Images | 1024 | 512 | Cosine Similarity, Dot Product Similarity, Euclidean Distance | Embed, Embed Jobs |
embed-multilingual-light-v3.0 |
A smaller, faster version of embed-multilingual-v3.0. Almost as capable, but a lot faster. Supports multiple languages. |
Text, Images | 384 | 512 | Cosine Similarity, Dot Product Similarity, Euclidean Distance | Embed, Embed Jobs |
List of Supported Languages
Section titled “List of Supported Languages”Our multilingual embed model supports over 100 languages, including Chinese, Spanish, and French.
| ISO Code | Language Name |
|---|---|
| af | Afrikaans |
| am | Amharic |
| ar | Arabic |
| as | Assamese |
| az | Azerbaijani |
| be | Belarusian |
| bg | Bulgarian |
| bn | Bengali |
| bo | Tibetan |
| bs | Bosnian |
| ca | Catalan |
| ceb | Cebuano |
| co | Corsican |
| cs | Czech |
| cy | Welsh |
| da | Danish |
| de | German |
| el | Greek |
| en | English |
| eo | Esperanto |
| es | Spanish |
| et | Estonian |
| eu | Basque |
| fa | Persian |
| fi | Finnish |
| fr | French |
| fy | Frisian |
| ga | Irish |
| gd | Scots_gaelic |
| gl | Galician |
| gu | Gujarati |
| ha | Hausa |
| haw | Hawaiian |
| he | Hebrew |
| hi | Hindi |
| hmn | Hmong |
| hr | Croatian |
| ht | Haitian_creole |
| hu | Hungarian |
| hy | Armenian |
| id | Indonesian |
| ig | Igbo |
| is | Icelandic |
| it | Italian |
| ja | Japanese |
| jv | Javanese |
| ka | Georgian |
| kk | Kazakh |
| km | Khmer |
| kn | Kannada |
| ko | Korean |
| ku | Kurdish |
| ky | Kyrgyz |
| La | Latin |
| Lb | Luxembourgish |
| Lo | Laothian |
| Lt | Lithuanian |
| Lv | Latvian |
| mg | Malagasy |
| mi | Maori |
| mk | Macedonian |
| ml | Malayalam |
| mn | Mongolian |
| mr | Marathi |
| ms | Malay |
| mt | Maltese |
| my | Burmese |
| ne | Nepali |
| nl | Dutch |
| no | Norwegian |
| ny | Nyanja |
| or | Oriya |
| pa | Punjabi |
| pl | Polish |
| pt | Portuguese |
| ro | Romanian |
| ru | Russian |
| rw | Kinyarwanda |
| si | Sinhalese |
| sk | Slovak |
| sl | Slovenian |
| sm | Samoan |
| sn | Shona |
| so | Somali |
| sq | Albanian |
| sr | Serbian |
| st | Sesotho |
| su | Sundanese |
| sv | Swedish |
| sw | Swahili |
| ta | Tamil |
| te | Telugu |
| tg | Tajik |
| th | Thai |
| tk | Turkmen |
| tl | Tagalog |
| tr | Turkish |
| tt | Tatar |
| ug | Uighur |
| uk | Ukrainian |
| ur | Urdu |
| uz | Uzbek |
| vi | Vietnamese |
| wo | Wolof |
| xh | Xhosa |
| yi | Yiddish |
| yo | Yoruba |
| zh | Chinese |
| zu | Zulu |
Frequently Asked Questions
Section titled “Frequently Asked Questions”What is the Context Length for Cohere Embeddings Models?
Section titled “What is the Context Length for Cohere Embeddings Models?”You can find the context length for various Cohere embeddings models in the tables above. It's in the "Max Tokens (Context Length)" column.