c4ai command r v01 4bit

Name: c4ai command r v01 4bit
Author: Cohere

by CohereCommand R

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

Released March 2024context N/A

A conversational model optimized for retrieval-augmented generation and tool use, Command R handles multi-step reasoning and grounded responses with a practical, workmanlike approach. It's built to stay connected to provided context rather than freelancing with its own knowledge, which makes it reliable when accuracy to source material matters. The 4-bit quantization means it runs on more modest hardware, though with some quality trade-offs compared to full precision.

Capabilities

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

Coding

Moderate

Tool Use

c4ai command r v01 4bit

by CohereCommand R

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

Released March 2024context N/A

A conversational model optimized for retrieval-augmented generation and tool use, Command R handles multi-step reasoning and grounded responses with a practical, workmanlike approach. It's built to stay connected to provided context rather than freelancing with its own knowledge, which makes it reliable when accuracy to source material matters. The 4-bit quantization means it runs on more modest hardware, though with some quality trade-offs compared to full precision.

Capabilities

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

Coding

Moderate

Tool Use

Glossary

4-bit QuantizationA specific type of quantization that represents model weights using only 4 bits instead of the original 32 bits, enabling very efficient inference on consumer hardware.Conversational ModelA language model specifically trained and optimized to engage in multi-turn dialogue with users.Multi-Step ReasoningThe ability to break down complex problems into smaller steps and solve them sequentially, rather than jumping directly to an answer.PrecisionThe level of numerical detail a model uses to represent its internal values; higher precision means more accurate calculations but requires more memory.QuantizationReducing a model's numerical precision (e.g., from 16-bit to 4-bit) to shrink memory usage and speed up inference.ReasoningThe model's ability to work through multi-step logical problems and provide justified answers rather than just pattern-matching.RetrievalThe process of finding and returning relevant documents or information from a database based on a query.Retrieval-AugmentedA technique that enhances AI systems by first searching for relevant information from a database before generating responses, improving accuracy and relevance.Retrieval-Augmented GenerationA technique that allows a model to search and reference external documents or knowledge bases to answer questions more accurately and with citations.Tool UseThe ability of a model to call external functions or APIs to perform tasks like calculations, searches, or data retrieval.

Capabilities

Capabilities

Use Case Fit

Glossary