from transformers import FlaxRobertaForMaskedLM, RobertaForMaskedLM, AutoTokenizer import jax import jax.numpy as jnp def to_f32(t): return jax.tree_map( lambda x: x.astype(jnp.float32) if x.dtype == jnp.bfloat16 else x, t ) # load flax fp16 model model = FlaxRobertaForMaskedLM.from_pretrained("./") # convert to fp32 model model.params = to_f32(model.params) # save flax fp32 model model.save_pretrained("./") # convert flax fp32 model to pytorch model_pt = RobertaForMaskedLM.from_pretrained("./", from_flax=True) model_pt.save_pretrained("./") tokenizer = AutoTokenizer.from_pretrained("./") tokenizer.save_pretrained("./")