Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsLLMsAI21Aleph AlphaAmazon API GatewayAnyscaleArceeAzure MLAzure OpenAIBaidu QianfanBananaBasetenBeamBedrockBittensorCerebriumAIChatGLMClarifaiCohereC TransformersCTranslate2DatabricksDeepInfraDeepSparseEden AIFireworksForefrontAIGCP Vertex AIGooseAIGPT4AllGradientHugging Face HubHugging Face Local PipelinesHuggingface TextGen InferenceJavelin AI Gateway TutorialJSONFormerKoboldAI APILlama.cppLLM Caching integrationsManifestMinimaxModalMosaicMLNLP CloudOctoAIOllamaOpaquePromptsOpenAIOpenLLMOpenLMPetalsPipelineAIPredibasePrediction GuardPromptLayer OpenAIRELLMReplicateRunhouseSageMakerEndpointStochasticAINebula (Symbl.ai)TextGenTitan TakeoffTogether AITongyi QwenvLLMWriterXorbits Inference (Xinference)YandexGPTChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAgents and toolkitsMemoryCallbacksChat loadersComponentsLLMsChatGLMChatGLMChatGLM-6B is an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level). ChatGLM2-6B is the second-generation version of the open-source bilingual (Chinese-English) chat model ChatGLM-6B. It retains the smooth conversation flow and low deployment threshold of the first-generation model, while introducing the new features like better performance, longer context and more efficient inference.This example goes over how to use LangChain to interact with ChatGLM2-6B Inference for text completion.
ChatGLM-6B is an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level).
ChatGLM-6B is an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level). ->: Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsLLMsAI21Aleph AlphaAmazon API GatewayAnyscaleArceeAzure MLAzure OpenAIBaidu QianfanBananaBasetenBeamBedrockBittensorCerebriumAIChatGLMClarifaiCohereC TransformersCTranslate2DatabricksDeepInfraDeepSparseEden AIFireworksForefrontAIGCP Vertex AIGooseAIGPT4AllGradientHugging Face HubHugging Face Local PipelinesHuggingface TextGen InferenceJavelin AI Gateway TutorialJSONFormerKoboldAI APILlama.cppLLM Caching integrationsManifestMinimaxModalMosaicMLNLP CloudOctoAIOllamaOpaquePromptsOpenAIOpenLLMOpenLMPetalsPipelineAIPredibasePrediction GuardPromptLayer OpenAIRELLMReplicateRunhouseSageMakerEndpointStochasticAINebula (Symbl.ai)TextGenTitan TakeoffTogether AITongyi QwenvLLMWriterXorbits Inference (Xinference)YandexGPTChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAgents and toolkitsMemoryCallbacksChat loadersComponentsLLMsChatGLMChatGLMChatGLM-6B is an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters. With the quantization technique, users can deploy locally on consumer-grade graphics cards (only 6GB of GPU memory is required at the INT4 quantization level). ChatGLM2-6B is the second-generation version of the open-source bilingual (Chinese-English) chat model ChatGLM-6B. It retains the smooth conversation flow and low deployment threshold of the first-generation model, while introducing the new features like better performance, longer context and more efficient inference.This example goes over how to use LangChain to interact with ChatGLM2-6B Inference for text completion.