File size: 1,919 Bytes
da43130 736efc3 b446cef da43130 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
license: mit
language:
- en
library_name: transformers
tags:
- 'vision '
- speech
- image-text-text
- audio-text-text
- Multi-Modal
---
# Creation Process
<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/65d883893a52cd9bcd8ab7cf/tRsCJlHNZo1D02kBTmfy9.jpeg" width="300"/>
Vmodel = VisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "LeroyDyer/Mixtral_AI_Tiny"
)
_Encoder_ImageProcessor = Vmodel.encoder
_Decoder_ImageTokenizer = Vmodel.decoder
_VisionEncoderDecoderModel = Vmodel
# Add Pad tokems
LM_MODEL.VisionEncoderDecoder = _VisionEncoderDecoderModel
# Add Sub Components
LM_MODEL.Encoder_ImageProcessor = _Encoder_ImageProcessor
LM_MODEL.Decoder_ImageTokenizer = _Decoder_ImageTokenizer
LM_MODEL
```
# ADD AUDIO
```python
print('Add Audio...')
#Add Head
# Combine pre-trained encoder and pre-trained decoder to form a Seq2Seq model
_AudioFeatureExtractor = AutoFeatureExtractor.from_pretrained("openai/whisper-small")
_AudioTokenizer = AutoTokenizer.from_pretrained("openai/whisper-small")
_SpeechEncoderDecoder = SpeechEncoderDecoderModel.from_encoder_decoder_pretrained("openai/whisper-small","openai/whisper-small")
# Add Pad tokems
_SpeechEncoderDecoder.config.decoder_start_token_id = _AudioTokenizer.cls_token_id
_SpeechEncoderDecoder.config.pad_token_id = _AudioTokenizer.pad_token_id
LM_MODEL.SpeechEncoderDecoder = _SpeechEncoderDecoder
# Add Sub Components
LM_MODEL.Decoder_AudioTokenizer = _AudioTokenizer
LM_MODEL.Encoder_AudioFeatureExtractor = _AudioFeatureExtractor
LM_MODEL
```
# SAVE
```python
print('Final stages:...')
print('Add tokenizer...')
LM_MODEL.resize_token_embeddings(len(tokenizer))
LM_MODEL.tokenizer = tokenizer
print('Save model...')
LM_MODEL.to(torch.float16)
LM_MODEL.save_pretrained("Mixtral_AI_MiniModalTron")
print('Save tokenizer...')
tokenizer.save_pretrained("Mixtral_AI_MiniModalTron")
``` |