Instructions to use InternScience/ChartVLM-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InternScience/ChartVLM-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InternScience/ChartVLM-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download auxiliary_decoder/base/config.json from InternScience/ChartVLM-large: direct link, hf CLI and curl.
- Browser
- Download file 638 Bytes
-
https://huggingface.co/InternScience/ChartVLM-large/resolve/main/auxiliary_decoder/base/config.json
- Command line
-
hf download hf://InternScience/ChartVLM-large/auxiliary_decoder/base/config.json
-
curl -L -o config.json https://huggingface.co/InternScience/ChartVLM-large/resolve/main/auxiliary_decoder/base/config.json
638 Bytes
| { | |
| "_name_or_path": "vicuna-13b-v1.5", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 5120, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 13824, | |
| "max_length": 4096, | |
| "max_position_embeddings": 4096, | |
| "model_type": "llama", | |
| "num_attention_heads": 40, | |
| "num_hidden_layers": 40, | |
| "num_key_value_heads": 40, | |
| "pad_token_id": 0, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.31.0", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |