'paraphrase-multilingual-MiniLM-L12-v2':SentenceModel(paraph_mul_path,device='cpu'), 'all-MiniLM-L12-v2':SentenceModel(all_mini_12_path,device='cpu'), } # keywords models Expand All@@ -427,6 +433,7 @@ def get_model_path(remote_path): ...
一个基于 MiniLM-L12-v2 架构的大型预训练语言模型。MiniLM-L12-v2 是 MiniLM 系列中的一种变体,具有更多的参数和更高的模型容量,适用于各种自然语言处理任务。
Copia fromlangchain.embeddingsimportHuggingFaceEmbeddingsembedding_model=HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L12-v2") Creare una connessione a OCI con OpenSearch utilizzando LangChain, specificando il nome dell'indice, il metodo di autenticazione e il modello di incorporament...
Copia fromlangchain.embeddingsimportHuggingFaceEmbeddingsembedding_model=HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L12-v2") Creare una connessione a OCI con OpenSearch utilizzando LangChain, specificando il nome dell'indice, il metodo di autenticazione e il modello di incorporament...
("sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2"), embed_model=AutoModel.from_pretrained("sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2") ) ), ) with open("results\prompts\abstract_summary.txt", encoding="utf8") as f: rag.insert(f.read()) import time start_time =...
ranker = Reranker('ce-esci-MiniLM-L12-v2', model_type='flashrank') # Default T5 Seq2Seq reranker ranker = Reranker("t5") # Specific T5 Seq2Seq reranker ranker = Reranker("unicamp-dl/InRanker-base", model_type = "t5") # API (Cohere) ranker = Reranker("cohere", lang='en' ...
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use. - gpt4all/gpt4all-backend/llamamodel.cpp at ccb98f34e0bf4497aa5069a04300a40e81f0f97b · nomic-ai/gpt4all
GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use. - gpt4all/gpt4all-backend/llamamodel.cpp at 636307160e69518cd285038b3a7699996b8bdd3d · nomic-ai/gpt4all
{"all-MiniLM-L6-v1", "all-MiniLM-L12-v1", "all-MiniLM-L6-v2", "all-MiniLM-L12-v2"}}, {NOMIC_SPEC, {"nomic-embed-text-v1", "nomic-embed-text-v1-ablated", "nomic-embed-text-v1-unsupervised"}}, {NOMIC_1_5_SPEC, {"nomic-embed-text-v1.5"}}, {LLM_EMBEDDE...