How does the API inference work on models such as Blenderbot?
I assume models like blenderbot need to look at prior inputs and outputs in order to form some consistency. How does the inference API provide that to the model?
2021-02-01T14:03:08Z
Hey, I’m dealing with the same subject.As far as I understand, there is a way to provide the context of the previous text in the conversation.The details are here:https://api-inference.huggingface.co/docs/python/html/detailed_parameters.html#conversational-taskAlthough, when I tried it on the 1B model, I’m getting the following error:“Cutting history off because it’s too long (36 > 28) for underlying model”I don’t know if this is a limitation of the model or the API.If you find a solution for that I let me know.
2022-05-12T10:59:28Z
Me too. I attempt to use the ‘template’ from conversational task / microsoft/dialoGPT to provide past_user_inputs and generated_responses, but it is not working.Some guidance on this will be appreciated
2022-05-12T11:11:01Z
Trouble Invoking GPU-Accelerated InferenceBeginnersWe recently signed up for an “Organization-Lab” account and are trying to use various blenderbot models available on hugging face with GPU-Accelerated Inference as referenced here: 

For example, we are calling 
https://api-inference.huggingface.co/models/facebook/blenderbot_small-90M 
with our org bearer token 
and input of 
{
  "inputs": {
    "past_user_inputs": null,
    "generated_responses": null,
    "text": "Hi, how are you today?"
  },
  "options": {
    "use_gpu": true,
    "use_cache"…It works.  Thanks
2022-05-14T07:53:35Z
soni69:It works. ThanksYeah, It is working.