ASSISTANTS
BLOCKS
BUNDLES
Blocks are reusable components that define specific behaviors and capabilities for AI assistants, from custom instructions to advanced model configurations
The following blocks are popular in the Continue community
Anthropic's most intelligent model with toggleable extended thinking
A meta-artificial intelligence infusion
DeepSeek R1 Distill Qwen 32B distils Qwen 2.5 and DeepSeek R1 expertise into a powerful 32B model. Outperforms OpenAI's o1-mini with impressive math capabilities (AIME: 72.6%, MATH-500: 94.3%) and coding skills (CodeForces: 1691).
free
hono-crud
Llama-3.2-1B-Instruct is Meta's compact multilingual model at 1B parameters. This instruction-tuned version balances efficiency with generative capabilities across multiple languages.
The latest series of Code-Specific Qwen models, with significant improvements in code generation, code reasoning, and code fixing
Google Coding Styles for Python
MythoMax L2 13B combines MythoLogic-L2's comprehension with Huginn's writing capabilities through innovative tensor merging. This 13B hybrid model balances robust understanding with creative expression.
Llama-3-70B-Instruct is Meta's instruction-tuned model at 70B parameters, trained on 15T tokens. This decoder-only architecture shows competitive dialogue performance against leading closed-source models.
I asked Claude to distill https://go.dev/doc/effective_go into a rules file.
Gemini's newest multimodal model, with next generation features and improved capabilities
OpenTelemetry, also known as OTel, is a vendor-neutral open source Observability framework for instrumenting, generating, collecting, and exporting telemetry data such as traces, metrics, and logs. As an industry-standard, OpenTelemetry is supported by more than 40 observability vendors, integrated by many libraries, services, and apps, and adopted by numerous end users.