Hi @martin-gorner -

Thanks for reporting the issue. You can intialize falcon-7b-instruct model using transformers AutoTokenizer, AutoModelForCausalLM class.

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_name = "tiiuae/falcon-7b-instruct"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, trust_remote_code=True, device_map="auto") 

And for loading falcon model family(falcon_refinedweb_1b_en) in keras-hub, you can use like this.
model5 = keras_hub.models.CausalLM.from_preset("hf://keras/falcon_refinedweb_1b_en", dtype="bfloat16")

Attached gist here for the reference.

This issue is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.

Thanks @mehtamansi29 but this issue is filed in keras-hub. The problem is to initialize a Keras-hub model from the safetensor checkpoint, as is possible for Llama, Gemma etc. I'm logging this because cross-compatibility between Keras-hub and Transformers checkpoints is not guaranteed even if the model architecture exists on both sides. A checkpoint translation module is necessary. It is important to keep track of model architectures where this translation module was implemented and where it was not.