Instructions to use Humayoun/CombinedInvoicesMerged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Humayoun/CombinedInvoicesMerged with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Humayoun/CombinedInvoicesMerged", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Humayoun/CombinedInvoicesMerged with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Humayoun/CombinedInvoicesMerged to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Humayoun/CombinedInvoicesMerged to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Humayoun/CombinedInvoicesMerged to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Humayoun/CombinedInvoicesMerged", max_seq_length=2048, )
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| "Gemma3ForConditionalGeneration" | |
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| "model_type": "gemma3", | |
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| "text_config": { | |
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| "attention_bias": false, | |
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| "cache_implementation": "hybrid", | |
| "final_logit_softcapping": null, | |
| "head_dim": 256, | |
| "hidden_activation": "gelu_pytorch_tanh", | |
| "hidden_size": 2560, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 10240, | |
| "layer_types": [ | |
| "sliding_attention", | |
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| "max_position_embeddings": 131072, | |
| "model_type": "gemma3_text", | |
| "num_attention_heads": 8, | |
| "num_hidden_layers": 34, | |
| "num_key_value_heads": 4, | |
| "query_pre_attn_scalar": 256, | |
| "rms_norm_eps": 1e-06, | |
| "rope_local_base_freq": 10000.0, | |
| "rope_scaling": { | |
| "factor": 8.0, | |
| "rope_type": "linear" | |
| }, | |
| "rope_theta": 1000000.0, | |
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| "torch_dtype": "bfloat16", | |
| "use_cache": true, | |
| "vocab_size": 262208 | |
| }, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.55.4", | |
| "unsloth_fixed": true, | |
| "unsloth_version": "2025.9.9", | |
| "vision_config": { | |
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| "hidden_act": "gelu_pytorch_tanh", | |
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| "image_size": 896, | |
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| "layer_norm_eps": 1e-06, | |
| "model_type": "siglip_vision_model", | |
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| "num_channels": 3, | |
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| "patch_size": 14, | |
| "torch_dtype": "bfloat16", | |
| "vision_use_head": false | |
| } | |
| } | |