new·The score now tells you which way it movedA brain's exam only ever grows: its own material writes questions, and so does every question a real caller asked and did not get answered. The score is a percentage over that growing set, so a brain that learned more could post a smaller number — and this week three did. One of them answered two MORE questions than the week before and showed eighteen points less. Printed as a single percentage, that reads as decline to a reader and as punishment to anyone who contributes material.all news →
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lmstudio/capabilities

6 notes, read out of this brain and free to use. Each one was extracted from a source and is re-checked against its exam.

LM Studio generateText example

Example using LM Studio with generateText: import { createOpenAICompatible } from '@ai-sdk/openai-compatible'; import { generateText } from 'ai'; const lmstudio = createOpenAICompatible({ name: 'lmstudio', baseURL: 'https://localhost:1234/v1' }); const { text } = await generateText({ model: lmstudio('llama-3.2-1b'), prompt: 'Write a vegetarian lasagna recipe for 4 people.', maxRetries: 1 });

LM Studio supports streamText

LM Studio language models can be used with the streamText function.

LM Studio embed single value example

Example using LM Studio with embed for a single value: import { createOpenAICompatible } from '@ai-sdk/openai-compatible'; import { embed } from 'ai'; const lmstudio = createOpenAICompatible({ name: 'lmstudio', baseURL: 'https://localhost:1234/v1' }); const { embedding } = await embed({ model: lmstudio.embeddingModel('text-embedding-nomic-embed-text-v1.5'), value: 'sunny day at the beach' });

LM Studio embedMany example

Example using LM Studio with embedMany for batch embedding: import { createOpenAICompatible } from '@ai-sdk/openai-compatible'; import { embedMany } from 'ai'; const lmstudio = createOpenAICompatible({ name: 'lmstudio', baseURL: 'https://localhost:1234/v1' }); const { embeddings } = await embedMany({ model: lmstudio.embeddingModel('text-embedding-nomic-embed-text-v1.5'), values: ['sunny day at the beach', 'rainy afternoon in the city', 'snowy night in the mountains'] });

LM Studio supports generateText and streamText

LM Studio language models can be used with both generateText and streamText functions from the AI SDK.

LM Studio supports embed and embedMany

LM Studio embedding models can be used with both embed (single value) and embedMany (batch) functions from the AI SDK.

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