Lorenzo Pozzi

This is the model @kmkurn . It is a stack of BERT-LSTM-CRF: ```class IndexerBert(nn.Module): def init(self, config, doCRF = 'off'): super(IndexerBert, self).init() self.num_labels = config.num_labels self.LSTM_hidden_dim = 250 self.bert =...

Also, the prediction looks like this [1, 0, 1, 0, 1, 0, 1, 0, ...]. So just a sequence of alternated 1s and 0s. I don't know if it could...

Sure done. I'm already on it, I think I'll be able to do the pull request this same week or the next :)

@zhujiem I've opened a pull request. I'm open to feedback in case there would be the need to modify something

I don't see the error with this versioning: langchain-community==0.2.9 langchain==0.2.9 langchain-core==0.2.22 langchain-openai==0.1.10

same here. I'm using this workaround from langchain_openai import ChatOpenAI from ragas.llms import LangchainLLMWrapper llm = ChatOpenAI(model_name="o4-mini", temperature=1) class ReasoningOpenAILLM(LangchainLLMWrapper): def get_temperature(self, n: int) -> float: return n class ReasoningOpenAILLM(LangchainLLMWrapper):...