Image-Text-to-Text
Transformers
Safetensors
isaac
text-generation
perceptron
issac-0.1
conversational
custom_code
Instructions to use PerceptronAI/Isaac-0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PerceptronAI/Isaac-0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="PerceptronAI/Isaac-0.1", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("PerceptronAI/Isaac-0.1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use PerceptronAI/Isaac-0.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PerceptronAI/Isaac-0.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PerceptronAI/Isaac-0.1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/PerceptronAI/Isaac-0.1
- SGLang
How to use PerceptronAI/Isaac-0.1 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "PerceptronAI/Isaac-0.1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PerceptronAI/Isaac-0.1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "PerceptronAI/Isaac-0.1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PerceptronAI/Isaac-0.1", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use PerceptronAI/Isaac-0.1 with Docker Model Runner:
docker model run hf.co/PerceptronAI/Isaac-0.1
Update processor_config.json
Browse files- processor_config.json +31 -200
processor_config.json
CHANGED
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"auto_map": {
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"AutoProcessor": "modular_isaac.IsaacProcessor"
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"config":
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"add_cross_attention": false,
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"architectures": [
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"attention_bias": false,
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"attention_dropout": 0.0,
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"auto_map": {
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"bos_token_id": 151643,
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"chunk_size_feed_forward": 0,
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"cross_attention_hidden_size": null,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"dtype": "float32",
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"early_stopping": false,
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"encoder_no_repeat_ngram_size": 0,
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"eos_token_id": 151645,
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"exponential_decay_length_penalty": null,
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"finetuning_task": null,
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"forced_bos_token_id": null,
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"forced_eos_token_id": null,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"id2label": {
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"initializer_range": 0.02,
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"intermediate_size": 6144,
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"is_decoder": false,
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"is_encoder_decoder": false,
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"num_key_value_heads": 8,
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"output_attentions": false,
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"pixel_shuffle_scale": 2,
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"repetition_penalty": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"rope_type": "default"
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"rope_theta": 1000000.0,
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"temperature": 1.0,
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"tf_legacy_loss": false,
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"tie_encoder_decoder": false,
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"tie_word_embeddings": false,
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"top_k": 50,
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"top_p": 1.0,
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"torchscript": false,
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"transformers_version": "4.56.1",
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"use_bfloat16": false,
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"use_cache": true,
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"video_patch_size": 16,
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"vision_config": {
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"add_cross_attention": false,
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"architectures": null,
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"chunk_size_feed_forward": 0,
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"diversity_penalty": 0.0,
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"do_sample": false,
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"forced_bos_token_id": null,
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"hidden_act": "gelu_pytorch_tanh",
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"hidden_size": 1152,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1"
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},
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"image_size": 256,
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"intermediate_size": 4304,
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"is_decoder": false,
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"is_encoder_decoder": false,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1
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},
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"layer_norm_eps": 1e-06,
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"length_penalty": 1.0,
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"max_length": 20,
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"min_length": 0,
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"model_type": "pixel_shuffle_siglip2",
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"num_attention_heads": 16,
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"num_beam_groups": 1,
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"num_beams": 1,
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"num_channels": 3,
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"num_hidden_layers": 27,
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"num_patches": 256,
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"num_return_sequences": 1,
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"output_attentions": false,
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"output_hidden_states": false,
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"output_scores": false,
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"pad_token_id": null,
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"patch_size": 16,
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"pixel_shuffle_scale_factor": 2,
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"prefix": null,
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"problem_type": null,
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"pruned_heads": {},
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"remove_invalid_values": false,
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"repetition_penalty": 1.0,
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"return_dict": true,
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"return_dict_in_generate": false,
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"sep_token_id": null,
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"suppress_tokens": null,
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"task_specific_params": null,
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"temperature": 1.0,
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"tf_legacy_loss": false,
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"tie_encoder_decoder": false,
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"tie_word_embeddings": true,
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"tokenizer_class": null,
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"top_k": 50,
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"top_p": 1.0,
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"torchscript": false,
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"typical_p": 1.0,
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"use_bfloat16": false
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},
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"vision_max_num_patches": 6144,
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"vision_min_num_patches": 256,
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"vision_token": "<image>",
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"vocab_size": 151936
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},
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"auto_map": {
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"AutoProcessor": "modular_isaac.IsaacProcessor"
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},
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"config": null,
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"image_processor": {
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"auto_map": {
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"AutoProcessor": "modular_isaac.IsaacProcessor",
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"AutoImageProcessor": "modular_isaac.IsaacImageProcessorFast"
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"data_format": "channels_first",
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"disable_grouping": false,
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"do_center_crop": false,
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_pad": false,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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],
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"image_processor_type": "IsaacImageProcessorFast",
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"image_std": [
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],
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"max_num_patches": 6144,
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"min_num_patches": 256,
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"patch_size": 16,
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"pixel_shuffle_scale": 2,
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"resample": 2,
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"rescale_factor": 0.00392156862745098
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},
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"max_sequence_length": 16384,
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"processor_class": "IsaacProcessor",
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"vision_token": "<image>"
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}
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