SANKAR N

Results 12 issues of SANKAR N

**Describe the bug** Integrate prediction explainer (predict.explain() using LIME, Local prediction explanation ) https://github.com/marcotcr/lime

The CSVReaderHeaderAware reader.readmap() function when reading a CSV file seems to have issues when the header names have either longer text or something related to it. Here are the details....

bug

Firstly, Thanks for developing this great model , the library and the demo at HuggingFace. My question is : Can we use Ru-dalle model using the HuggingFace Accelerated inference API...

@ThilinaRajapakse Can we use ProphetNet as a part of seq2seq model ? https://huggingface.co/docs/transformers/model_doc/prophetnet If not, Kindly add it as a feature under Seq2Seq in Simpletransformers i.e. to Predict and output...

stale

Hi, Can Tensile be deployed on the Amazon EC2 F1 / FPGA instance? https://aws.amazon.com/ec2/instance-types/f1/ https://github.com/aws/aws-fpga#getting-familiar-with-aws If it is possible , Kindly provide documentation and steps. I would like to try...

This is a separate issue created from the discussion by @nsankar addressed to @wong-a from the issue id #31 The key point is which are the common SFN and AWS...

documentation

@OscarEngelbrektson Thanks for developing this great package. Qualitatively, What is the causal **interpretation** for the pointwise and cumulative counterfactual prediction plots given in the Germany example ? Kindly elaborate For...

@Vincent-Vercruyssen Just a follow up my question from transfertools , Is it correct to assume that for the following code line I took from SSDO detector.fit_predict(Xtr, y, prior=tr_prior) ? -...

@Vincent-Vercruyssen Thanks for the great research and this package. I have a question on the transfer learning source, targets and transfer learning when using LocIT. **My scenario #1** is that...

Please include ChatGPT Turbo's ChatOpenAI object to be passed as an LLM completion in the Summarizer chain. _(from langchain.chat_models.openai import ChatOpenAI)_ for the following usage `summary_chain = load_summarize_chain(llm, chain_type="map_reduce") summarize_document_chain...