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Question: the response I got by using terminal is way better than using ollama.generate #65
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Originally created by @wangyeye66 on GitHub (Apr 12, 2024).
I use llama2 7b to for text generation. The prompt I attampted:
"""Task: Turn the input into (subject, predicate, object).
Input: Sam Johnson is eating breakfast.
Output: (Dolores Murphy, eat, breakfast)
Input: Joon Park is brewing coffee.
Output: (Joon Park, brew, coffee)
Input: Jane Cook is sleeping.
Output: (Jane Cook, is, sleep)
Input: Michael Bernstein is writing email on a computer.
Output: (Michael Bernstein, write, email)
Input: Percy Liang is teaching students in a classroom.
Output: (Percy Liang, teach, students)
Input: Merrie Morris is running on a treadmill.
Output: (Merrie Morris, run, treadmill)
Input: John Doe is drinking coffee.
Output: (John Doe,"""
using ollama.generate will generate a chat rather than keep generating the text.
In terminal, it seems understand what I would like to do. Did I call wrong function in python? How can I let the model know I don't need a chat-like response?
@93andresen commented on GitHub (Apr 13, 2024):
I've never tried this libary, but maybe "ollama.chat" works like the terminal amd "ollama.generate" is like autocomplete?
@ioo0s commented on GitHub (Jun 3, 2024):
I have the same problem, and the results I get from running it through the
ollama run xxmodelterminal are much better than the results I get from python sdkclient.chat. Why?@BowenKwan commented on GitHub (Jun 13, 2024):
Same problem here. Using
ollama run custom_modelin the terminal gives a much better result thanollama.chat(model='custom_model.It seems to me that all the few shot example provided in the modelfile used to train the custom_model is not provided to the custom model when using
ollama.chat. The result seems to be just like using the base model that the custom model is trained on.@mxyng commented on GitHub (Jun 13, 2024):
@wangyeye66 can you paste the output you get from the cli and the output from the
ollama.chat?from what I can tell, this behavior is expected. llama2:7b implements a chat template which uses these messages to simulate a user/assistant exchange. this is regardless of what method is used to interact with the llm,
cli,ollama.generate, orollama.chat. here's (roughly) what your prompt will produce as an input to the llm:based on your prompt, you're probably more interested in the text completion model, llama2:7b-text, which does not template the input
@mxyng commented on GitHub (Jun 13, 2024):
@BowenKwan your issue appears different so I'll respond in #188