MINI AI
Collection
The mini AI series ; I found that i needed smaller models for other models such as VisionEncoderDecoder : and other models which contain llms as a par • 5 items • Updated
Image-to-Text
Transformers
Safetensors
English
mistral
text-generation
vision
VISION-ENCODER-DECODER-MODEL
text-generation-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/SpydazWebAI_VisionEncoderDecoderModel_Mini548m")
model = AutoModelForCausalLM.from_pretrained("LeroyDyer/SpydazWebAI_VisionEncoderDecoderModel_Mini548m")Quick Links
ADD HEAD
Mistral
VISION-ENCODER-DECODER-MODEL
print('Add Vision...')
# ADD HEAD
# Combine pre-trained encoder and pre-trained decoder to form a Seq2Seq model
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
- Downloads last month
- 38
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="LeroyDyer/SpydazWebAI_VisionEncoderDecoderModel_Mini548m")