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Other LORA models #60
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sure thing! @philwee It shows "unsupported" since I have not tested the model. Please let me know where the model is(apparently you pointed it), well working cases(or how to structure the prompts). I assume you followed the same structure as in the original Alpaca dataset, yes? |
I manage prompt interfaces for different models in different repositories(for example plain Alpaca), if you think this one exactly matches to yours, please let me know |
It's based on basically plain alpaca, so it should work with the same stuff as alpaca - happy to test it once support is given (i have both a 7b and 13b adapter). Thank you for your help! |
Absolutely! Will let you know when I integrate them :) pretty soon |
hey @philwee , can you share the GenerationConfig that you used? Generated text on "hello" Hello, what is your name? | What can I do for you today.J it depends a lot on how specific are you with detail! Tell me your need. |
hi @deep-diver - I tested it using tloen/alpaca-lora's generate.py, which defaults to using following prompt:
More info can be found here: alpaca-lora prompts Right now, I just tested it - when I give it the input of "hello", I get "Hello! How can I help you today?", which seems alright - see below: Please let me know if this works, otherwise, happy to try to help. |
I see, the Generation config is so different. let me check |
I think I can make this model works with just a simple case (1, 1, 1 instruction, input, and response). I have found that it is hard to inject past conversation history in the However, in your model's case, it looks it doesn't work if I don't follow the standard template format. hm... gotta think about this any further to make your model to work better. |
I think it was intended to be used in an alpaca like style anyway (1 input, 1 output) - and the data that it was trained on was like that anyway. For now, I think that simple case would still be nice to have! :) I can also try to fine tune another version that focuses on a more conversational style - I'll update you once I've worked on it. |
For sure! How would you format dataset to reflect conversational style? |
probably I will include your model as a single turn conversation since I plan to add |
So I initially finetuned it using data in the format instruction-input-output (as is needed by alpaca-lora) For example:
A more conversation like format would involve data that looks something like this (note the delimiters [|Human|] and [|AI|])
(in my testing, the training with the conversation style-like data appears to result in better chat output, especially more than 1q+1a, than the instruction-input-output format) |
cool, thank you! stack llama is a nice approach too (in that it uses RLHF) |
Update: I've finetuned another model with data in a more conversational format: https://huggingface.co/couchpotato888/baize7bdollylora |
Would it be possible to support other LORA adapters?
For example, I've finetuned llama on alpaca + dolly (https://huggingface.co/couchpotato888/dolpaca_gpt4_13b_1e_adapter/tree/main) but I can't seem to use it on your Colab (it tells me it's unsupported) - it would be really nice if I could use your interface with my finetune.
Thanks for the great work on it btw, the interface looks really nice!
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