[SOLVED] How to convert pretrained hugging face model to .pt and run it fully locally?

How to convert pretrained hugging face model to .pt and run it fully locally?

I'm attempting to convert this model in .pt format. It's working fine for me so i dont want to fine-tune it. How can i export it to .pt and run interface?

I tried using this to convert to .pt:

from transformers import AutoConfig, AutoProcessor, AutoModelForCTC, AutoTokenizer, Wav2Vec2Processor
import librosa
import torch



# Define the model name
model_name = "UrukHan/wav2vec2-russian"

# Load the model and tokenizer
config = AutoConfig.from_pretrained(model_name)
model = AutoModelForCTC.from_pretrained(model_name, config=config)
processor = Wav2Vec2Processor.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Save the model as a .pt file
torch.save(model.state_dict(), "model.pt")

# Save the tokenizer as well if needed
tokenizer.save_pretrained("model-tokenizer")

but unfortunately its not running the interface :

model = AutoModelForCTC.from_pretrained("model.pt")
processor = AutoProcessor.from_pretrained("model.pt")


# Perform inference with the model
FILE = 'here is wav.wav'
audio, _ = librosa.load(FILE, sr = 16000)
audio = list(audio)
def map_to_result(batch):
  with torch.no_grad():
    input_values = torch.tensor(batch, device="cpu").unsqueeze(0) #, device="cuda"
    logits = model(input_values).logits
  pred_ids = torch.argmax(logits, dim=-1)
  batch = processor.batch_decode(pred_ids)[0]
  return batch
map_to_result(audio)
print(map_to_result(audio))


model.eval()

And encountered an error: `model.pt is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'

Solution

So, the solution was to save model and it's weights by using save_pretrained not by torch.save()