NousResearch

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OLMo-Bitnet-1B

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To load the model in google colab

!pip install omegaconf
!pip install botocore boto3 cached_path
!pip install accelerate

Then load model as given in Model CArd:

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, TextStreamer

tokenizer = AutoTokenizer.from_pretrained("NousResearch/OLMo-Bitnet-1B")
model = AutoModelForCausalLM.from_pretrained("NousResearch/OLMo-Bitnet-1B",
    torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto")

streamer = TextStreamer(tokenizer)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, 
                pad_token_id=tokenizer.eos_token_id,
    temperature=0.8, repetition_penalty=1.1, do_sample=True,streamer=streamer)
pipe("The capitol of Paris is",  max_new_tokens=256)

This gives error: KeyError: 'cache_position'

What is happening. How is it passing cache_position?

I upgraded transformers model but I kept getting other error like:

ValueError: 'olmo' is already used by a Transformers config, pick another name.