ollama/template.py
2023-06-26 13:41:16 -04:00

58 lines
1.4 KiB
Python

from difflib import SequenceMatcher
model_prompts = {
"alpaca": """Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
{prompt}
### Response:
""",
"oasst": "<|prompter|>{prompt}<|endoftext|><|assistant|>",
"vicuna": """A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
USER: {prompt}
ASSISTANT:""",
"hermes": """### Instruction:
{prompt}
### Response:
""",
"gpt4": """### Instruction:
{prompt}
### Response:
""",
"qlora": """### Human: {prompt}
### Assistant:""",
"tulu": """<|user|>
{prompt}
<|assistant|>
(include newline)""",
"wizardlm-7b": """{prompt}
### Response:""",
"wizardlm-13b": """{prompt}
### Response:""",
"wizardlm-30b": """{prompt}
### Response:""",
}
def template(model, prompt):
max_ratio = 0
closest_key = ""
model_name = model.lower()
# Find the specialized prompt with the closest name match
for key in model_prompts.keys():
ratio = SequenceMatcher(None, model_name, key).ratio()
if ratio > max_ratio:
max_ratio = ratio
closest_key = key
# Return the value of the closest match
p = model_prompts.get(closest_key) # .format(placeholder=prompt)
return p.format(prompt=prompt)