Image-to-Text
Transformers
Safetensors
English
mistral
text-generation
vision
VISION-ENCODER-DECODER-MODEL
text-generation-inference
Instructions to use LeroyDyer/SpydazWebAI_VisionEncoderDecoderModel_Mini548m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeroyDyer/SpydazWebAI_VisionEncoderDecoderModel_Mini548m with Transformers:
# 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")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/SpydazWebAI_VisionEncoderDecoderModel_Mini548m") model = AutoModelForCausalLM.from_pretrained("LeroyDyer/SpydazWebAI_VisionEncoderDecoderModel_Mini548m") - Notebooks
- Google Colab
- Kaggle
File size: 638 Bytes
c1b137b | 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 | {
"_name_or_path": "LeroyDyer/Mixtral_AI_Tiny",
"architectures": [
"MistralForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"max_position_embeddings": 32768,
"model_type": "mistral",
"num_attention_heads": 32,
"num_hidden_layers": 12,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-06,
"rope_theta": 10000.0,
"sliding_window": 32,
"tie_word_embeddings": false,
"torch_dtype": "float16",
"transformers_version": "4.38.2",
"use_cache": true,
"vocab_size": 32009
}
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