GritLM 7B vllm

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

Released February 202433K context≈ 24,576 words7B params

GritLM 7B is a dual-purpose model that handles both text generation and text embedding within a single set of weights — a relatively rare combination. It can produce embeddings for retrieval or similarity tasks and also generate coherent text responses, without needing separate models for each job. The trade-off is that it's a generalist in both roles rather than a specialist in either.

Capabilities

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

Instruction Following

Moderate

Tool Use

GritLM 7B vllm

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

Released February 202433K context≈ 24,576 words7B params

GritLM 7B is a dual-purpose model that handles both text generation and text embedding within a single set of weights — a relatively rare combination. It can produce embeddings for retrieval or similarity tasks and also generate coherent text responses, without needing separate models for each job. The trade-off is that it's a generalist in both roles rather than a specialist in either.

Capabilities

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

Instruction Following

Moderate

Tool Use

Glossary

Dual-Purpose ModelA single model trained to perform multiple distinct tasks, such as both text generation and embedding, rather than being specialized for just one.EmbeddingA dense numerical vector that represents a word, sentence, or concept in a high-dimensional space.EmbeddingsNumerical representations of text that capture semantic meaning, allowing the model to measure similarity between different words or phrases.RetrievalThe process of finding and returning relevant documents or information from a database based on a query.Text EmbeddingA technique that converts text into numerical vectors that capture semantic meaning, allowing the model to understand and compare text similarity.Text GenerationThe process of an AI model creating new text one word or token at a time based on patterns it learned during training.WeightsThe numerical parameters inside a neural network that determine how it processes input and generates output.

GritLM 7B vllm

Capabilities

GritLM 7B vllm

Capabilities

Use Case Fit

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Glossary