Hub 上的 Git 操作不再支持使用密码验证 (huggingface.co)Embedding models · Ollama Blogollama/docs/import.md at main · ollama/ollama · GitHub1、对通过 Git 与 Hugging Face Hub 交互时的认证方式进行更改。从 2023 年 10 月 1 日 开始,我们将 git 访问令牌 替代密码 Databend x HuggingFace,海...
from transformers import AutoConfig, Wav2Vec2FeatureExtractor from src.models import Wav2Vec2ForSpeechClassification, HubertForSpeechClassification #dataset: AVDESS model_name_or_path = "Rajaram1996/Hubert_emotion" device = torch.device("cuda" if torch.cuda.is_available() else "cpu") config = ...
BGE-LLM Embedder (Retrieve Anything To Augment Large Language Models)【2】 智源发布三款BGE新模型,再次刷新向量检索最佳水平 BGE M3-Embedding Monarch Mixer(M2) e5-mistral-7b-instruct Jina ColBERT v2 可视化工具Gradio 检索模型排行榜 1.word2vec ,使用单层神经网络,通过几个周围单词预测中心单词,但是这几...
这里做了三组实验,短文本匹配长文本,短文本匹配长文本,(instruction+)短文本匹配长文本。 fromsentence_transformersimportSentenceTransformerimportnumpyasnp# 直接使用hugging face# model = SentenceTransformer('moka-ai/m3e-base')# 下载模型到本地,放在models目录下面model=SentenceTransformer('models/bge')# this ...
Is there something which I absolutely have to do differently when using the huggingface models, or maybe there is a specific model on HF which is better for this sort of retrieval? Ill put the embedding code and sql query below in case something is blatantly wrong with it bu...
RuntimeError: Failed to import transformers.models.bert.modeling_bert because of the following error (look up to see its traceback): module 'torch._subclasses' has no attribute 'functional_tensor'This is happening when I am trying to load the reranker as well.from...
Lines 18 to 30 in f678243 class MLTask(str, Enum): """ Task defines the common ML tasks using Huggingface Transformer Models """ table_question_answering = auto() question_answering = auto() token_classification = auto() sequence_classification = auto() fill_mask = auto()...
通义千问:RAG(Retrieve and Ground)模型是Hugging Face提出的一种结合检索与生成的预训练模型,它在实现过程中应用了多种embedding技术来处理文本数据。以下是RAG中涉及的embedding技术: BERT-style Embeddings: o RAG通常利用BERT、RoBERTa或其他Transformer架构的预训练模型作为其基础模块,这些模型提供了对输入序列进行编码...
我们依靠OpenAI的GPT-3.5-turbo-0125模式来完成这项任务,该模式是OpenAI该系列的旗舰模型,支持16K上下文窗口并针对对话进行了优化(https://platform.openai.com/docs/models/gpt-3-5-turbo。 结果对象’ qa_dataset ‘包含问题和答案(块)对。作为生成问题的示例,以下是前两个问题的结果(其中“答案”是文本的第一...
· Hugging Face 代码:GitHub - nomic-ai/contrastors: Train Models Contrastively in Pytorch ...