Package dev.langchain4j.model.workersai
Enum Class WorkersAiChatModelName
- All Implemented Interfaces:
Serializable,Comparable<WorkersAiChatModelName>,Constable
Enum for Workers AI Chat Model Name.
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Nested Class Summary
Nested classes/interfaces inherited from class java.lang.Enum
Enum.EnumDesc<E extends Enum<E>> -
Enum Constant Summary
Enum ConstantsEnum ConstantDescriptionInstruct fine-tuned version of the Mistral-7b generative text model with 7 billion parameters.Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese..Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese..DeepSeekMath is initialized with DeepSeek-Coder-v1.5 7B and continues pre-training on math-related tokens sourced from Common Crawl, together with natural language and code data for 500B tokens.DiscoLM German 7b is a Mistral-based large language model with a focus on German-language applications.Falcon-7B-Instruct is a 7B parameters causal decoder-only model built by TII based on Falcon-7B and finetuned on a mixture of chat/instruct datasets.This is a Gemma-2B base model that Cloudflare dedicates for inference with LoRA adapters.This is a Gemma-7B base model that Cloudflare dedicates for inference with LoRA adapters.Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models.Hermes 2 Pro on Mistral 7B is the new flagship 7B Hermes! Hermes 2 Pro is an upgraded, retrained version of Nous Hermes 2, consisting of an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset developed in-house.Llama 2 13B Chat AWQ is an efficient, accurate and blazing-fast low-bit weight quantized Llama 2 variant.Quantized (int4) generative text model with 8 billion parameters from Meta.This is a Llama2 base model that Cloudflare dedicated for inference with LoRA adapters.Generation over generation, Meta Llama 3 demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including improved reasoning.Full precision (fp16) generative text model with 7 billion parameters from Met.Quantized (int8) generative text model with 7 billion parameters from Meta.Llama Guard is a model for classifying the safety of LLM prompts and responses, using a taxonomy of safety risks.Quantized (int4) generative text model with 8 billion parameters from Meta.DeepSeekMath-Instruct 7B is a mathematically instructed tuning model derived from DeepSeekMath-Base 7B.Mistral 7B Instruct v0.1 AWQ is an efficient, accurate and blazing-fast low-bit weight quantized Mistral variant.The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.2.The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.2.This model is a fine-tuned 7B parameter LLM on the Intel Gaudi 2 processor from the mistralai/Mistral-7B-v0.1 on the open source dataset Open-Orca/SlimOrca.OpenChat is an innovative library of open-source language models, fine-tuned with C-RLFT - a strategy inspired by offline reinforcement learning.OpenHermes 2.5 Mistral 7B is a state of the art Mistral Fine-tune, a continuation of OpenHermes 2 model, which trained on additional code datasets.Phi-2 is a Transformer-based model with a next-word prediction objective, trained on 1.4T tokens from multiple passes on a mixture of Synthetic and Web datasets for NLP and coding.Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud.Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud.Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud.Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud.This model is intended to be used by non-technical users to understand data inside their SQL databases.We introduce Starling-LM-7B-beta, an open large language model (LLM) trained by Reinforcement Learning from AI Feedback (RLAIF).The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens.Cybertron 7B v2 is a 7B MistralAI based model, best on it’s series.Zephyr 7B Beta AWQ is an efficient, accurate and blazing-fast low-bit weight quantized Zephyr model variant. -
Method Summary
Modifier and TypeMethodDescriptiontoString()static WorkersAiChatModelNameReturns the enum constant of this class with the specified name.static WorkersAiChatModelName[]values()Returns an array containing the constants of this enum class, in the order they are declared.
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Enum Constant Details
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LLAMA2_7B_FULL
Full precision (fp16) generative text model with 7 billion parameters from Met. -
LLAMA2_7B_QUANTIZED
Quantized (int8) generative text model with 7 billion parameters from Meta. -
CODELLAMA_7B_AWQ
Instruct fine-tuned version of the Mistral-7b generative text model with 7 billion parameters. -
DEEPSEEK_CODER_6_7_BASE
Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese.. -
DEEPSEEK_CODER_MATH_7B_AWQ
Deepseek Coder is composed of a series of code language models, each trained from scratch on 2T tokens, with a composition of 87% code and 13% natural language in both English and Chinese.. -
DEEPSEEK_CODER_MATH_7B_INSTRUCT
DeepSeekMath is initialized with DeepSeek-Coder-v1.5 7B and continues pre-training on math-related tokens sourced from Common Crawl, together with natural language and code data for 500B tokens. -
MISTRAL_7B_INSTRUCT
DeepSeekMath-Instruct 7B is a mathematically instructed tuning model derived from DeepSeekMath-Base 7B. DeepSeekMath is initialized with DeepSeek-Coder-v1.5 7B and continues pre-training on math-related tokens sourced from Common Crawl, together with natural language and code data for 500B tokens.. -
DISCOLM_GERMAN_7B_V1_AWQ
DiscoLM German 7b is a Mistral-based large language model with a focus on German-language applications. AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. -
FALCOM_7B_INSTRUCT
Falcon-7B-Instruct is a 7B parameters causal decoder-only model built by TII based on Falcon-7B and finetuned on a mixture of chat/instruct datasets. -
GEMMA_2B_IT_LORA
This is a Gemma-2B base model that Cloudflare dedicates for inference with LoRA adapters. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. -
GEMMA_7B_IT
Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. They are text-to-text, decoder-only large language models, available in English, with open weights, pre-trained variants, and instruction-tuned variants. -
GEMMA_2B_IT_LORA_DUPLICATE
This is a Gemma-7B base model that Cloudflare dedicates for inference with LoRA adapters. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. -
HERMES_2_PRO_MISTRAL_7B
Hermes 2 Pro on Mistral 7B is the new flagship 7B Hermes! Hermes 2 Pro is an upgraded, retrained version of Nous Hermes 2, consisting of an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset developed in-house. -
LLAMA_2_13B_CHAT_AWQ
Llama 2 13B Chat AWQ is an efficient, accurate and blazing-fast low-bit weight quantized Llama 2 variant. -
LLAMA_2_7B_CHAT_HF_LORA
This is a Llama2 base model that Cloudflare dedicated for inference with LoRA adapters. Llama 2 is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 70 billion parameters. This is the repository for the 7B fine-tuned model, optimized for dialogue use cases and converted for the Hugging Face Transformers format. -
LLAMA_3_8B_INSTRUCT
Generation over generation, Meta Llama 3 demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including improved reasoning. -
LLAMA_2_13B_CHAT_AWQ_DUPLICATE
Quantized (int4) generative text model with 8 billion parameters from Meta. -
LLAMAGUARD_7B_AWQ
Llama Guard is a model for classifying the safety of LLM prompts and responses, using a taxonomy of safety risks. -
META_LLAMA_3_8B_INSTRUCT
Quantized (int4) generative text model with 8 billion parameters from Meta. -
MISTRAL_7B_INSTRUCT_V0_1_AWQ
Mistral 7B Instruct v0.1 AWQ is an efficient, accurate and blazing-fast low-bit weight quantized Mistral variant. -
MISTRAL_7B_INSTRUCT_V0_2
The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.2. Mistral-7B-v0.2 has the following changes compared to Mistral-7B-v0.1: 32k context window (vs 8k context in v0.1), rope-theta = 1e6, and no Sliding-Window Attention. -
MISTRAL_7B_INSTRUCT_V0_2_LORA
The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.2. -
NEURAL_CHAT_7B_V3_1_AWQ
This model is a fine-tuned 7B parameter LLM on the Intel Gaudi 2 processor from the mistralai/Mistral-7B-v0.1 on the open source dataset Open-Orca/SlimOrca. -
OPENCHAT_3_5_0106
OpenChat is an innovative library of open-source language models, fine-tuned with C-RLFT - a strategy inspired by offline reinforcement learning. -
OPENHERMES_2_5_MISTRAL_7B_AWQ
OpenHermes 2.5 Mistral 7B is a state of the art Mistral Fine-tune, a continuation of OpenHermes 2 model, which trained on additional code datasets. -
PHI_2
Phi-2 is a Transformer-based model with a next-word prediction objective, trained on 1.4T tokens from multiple passes on a mixture of Synthetic and Web datasets for NLP and coding. -
QWEN1_5_0_5B_CHAT
Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud. -
QWEN1_5_1_8B_CHAT
Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud. -
QWEN1_5_14B_CHAT_AWQ
Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud. AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. -
QWEN1_5_7B_CHAT_AWQ
Qwen1.5 is the improved version of Qwen, the large language model series developed by Alibaba Cloud. AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. -
SQLCODER_7B_2
This model is intended to be used by non-technical users to understand data inside their SQL databases. -
STARLING_LM_7B_BETA
We introduce Starling-LM-7B-beta, an open large language model (LLM) trained by Reinforcement Learning from AI Feedback (RLAIF). Starling-LM-7B-beta is trained from Openchat-3.5-0106 with our new reward model Nexusflow/Starling-RM-34B and policy optimization method Fine-Tuning Language Models from Human Preferences (PPO). -
TINYLLAMA_1_1B_CHAT_V1_0
The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. This is the chat model finetuned on top of TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T. -
UNA_CYBERTRON_7B_V2_BF16
Cybertron 7B v2 is a 7B MistralAI based model, best on it’s series. It was trained with SFT, DPO and UNA (Unified Neural Alignment) on multiple datasets. -
ZEPHYR_7B_BETA_AWQ
Zephyr 7B Beta AWQ is an efficient, accurate and blazing-fast low-bit weight quantized Zephyr model variant.
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Method Details
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values
Returns an array containing the constants of this enum class, in the order they are declared.- Returns:
- an array containing the constants of this enum class, in the order they are declared
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valueOf
Returns the enum constant of this class with the specified name. The string must match exactly an identifier used to declare an enum constant in this class. (Extraneous whitespace characters are not permitted.)- Parameters:
name- the name of the enum constant to be returned.- Returns:
- the enum constant with the specified name
- Throws:
IllegalArgumentException- if this enum class has no constant with the specified nameNullPointerException- if the argument is null
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toString
- Overrides:
toStringin classEnum<WorkersAiChatModelName>
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