contriever msmarco

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released March 20221K context≈ 384 words

Contriever MSMbenchmarksO is a retrieval specialist — it converts text into dense vector embeddings optimized for finding semantically relevant passages. Fine-tuned on the MSMbenchmarksO passage dataset, it handles real-world web query patterns well, making it more grounded in practical search behavior than its base counterpart. Its 512-token context limit means long documents need chunking before it can process them.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Tool Use

Moderate

Instruction Following

contriever msmarco

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released March 20221K context≈ 384 words

Contriever MSMbenchmarksO is a retrieval specialist — it converts text into dense vector embeddings optimized for finding semantically relevant passages. Fine-tuned on the MSMbenchmarksO passage dataset, it handles real-world web query patterns well, making it more grounded in practical search behavior than its base counterpart. Its 512-token context limit means long documents need chunking before it can process them.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Tool Use

Moderate

Instruction Following

Glossary

ChunkingThe process of breaking large documents into smaller pieces so a model with a limited context window can process them separately.Dense VectorA compact numerical representation where most values are non-zero, used to efficiently store and compare the meaning of text.Dense Vector EmbeddingsNumerical representations of text where each word or sentence is converted into a list of numbers that capture its meaning, allowing the model to compare semantic similarity.EmbeddingsNumerical representations of text that capture semantic meaning, allowing the model to measure similarity between different words or phrases.Fine-TunedA pre-trained model further trained on a smaller, task-specific dataset to improve performance on that task.RetrievalThe process of finding and returning relevant documents or information from a database based on a query.TokenA small unit of text (a word, subword, or punctuation mark) that a language model breaks input into for processing.Vector EmbeddingsNumerical representations of text where each word or sentence becomes a list of numbers that capture its meaning in a way computers can process.

contriever msmarco

Capabilities

contriever msmarco

Capabilities

Use Case Fit

Similar Models

Glossary