Error: `rope_scaling`must be a dictionary with two fields
#1
by
LeMoussel
- opened
I ran the code:
import torch
from transformers import AutoTokenizer, LlamaConfig, LlamaForCausalLM
# YaRN: Efficient Context Window Extension of Large Language Models: https://github.com/jquesnelle/yarn
# https://huggingface.co/NousResearch/Yarn-Llama-2-7b-64k
model_path = "NousResearch/Yarn-Llama-2-7b-64k"
tokenizer = AutoTokenizer.from_pretrained(model_path)
config = LlamaConfig.from_pretrained(model_path, trust_remote_code=True)
model = LlamaForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloat16, device_map="auto", config=config, trust_remote_code=True)
Then, I got the error:
The argument `trust_remote_code` is to be used with Auto classes. It has no effect here and is ignored.
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-4-cb4c3c69fc36> in <cell line: 9>()
7
8 tokenizer = AutoTokenizer.from_pretrained(model_path)
----> 9 config = LlamaConfig.from_pretrained(model_path, trust_remote_code=True)
10 model = LlamaForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloat16, device_map="auto", config=config, trust_remote_code=True)
3 frames
/usr/local/lib/python3.10/dist-packages/transformers/models/llama/configuration_llama.py in _rope_scaling_validation(self)
174
175 if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2:
--> 176 raise ValueError(
177 "`rope_scaling` must be a dictionary with with two fields, `type` and `factor`, "
178 f"got {self.rope_scaling}"
ValueError: `rope_scaling` must be a dictionary with with two fields, `type` and `factor`, got {'factor': 16.0, 'original_max_position_embeddings': 4096, 'type': 'yarn', 'finetuned': True}
Thanks in advance for your help.
LeMoussel
changed discussion title from
Error: `rope_scaling`must be a dictionary with with two fields
to Error: `rope_scaling`must be a dictionary with two fields
Hey @LeMoussel , did you ever get the solution to this error?
Nope.I dropped
You are using the transformers to load the model, which using the default modelling_llama script. There is a script in the files provided. Try running the model with that.
What script are you talking about? Is it configuration_llama.py
?
Do you have an example of how to use this script to running the model with that?
LeMoussel
changed discussion status to
closed