Feature Extraction
Transformers
Safetensors
multilingual
neomme
multimodal
document-understanding
masked-language-modeling
long-context
Instructions to use Hcompany/NeoMME-800M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hcompany/NeoMME-800M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Hcompany/NeoMME-800M")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("Hcompany/NeoMME-800M") model = AutoModel.from_pretrained("Hcompany/NeoMME-800M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from Hcompany/NeoMME-800M: direct link, hf CLI and curl.
- Browser
- Download file 485 Bytes
-
https://huggingface.co/Hcompany/NeoMME-800M/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://Hcompany/NeoMME-800M/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Hcompany/NeoMME-800M/resolve/main/tokenizer_config.json
485 Bytes
| { | |
| "backend": "tokenizers", | |
| "clean_up_tokenization_spaces": false, | |
| "document_token": "<doc>", | |
| "eos_token": "<eos>", | |
| "extra_special_tokens": [], | |
| "image_token": "<img>", | |
| "mask_token": "<mask>", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 16384, | |
| "pad_token": "<pad>", | |
| "processor_class": "NeoMMEProcessor", | |
| "query_token": "<query>", | |
| "row_token": "<row>", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>" | |
| } | |