Instructions to use 5CD-AI/ColVintern-1B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 5CD-AI/ColVintern-1B-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="5CD-AI/ColVintern-1B-v1", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("5CD-AI/ColVintern-1B-v1", trust_remote_code=True, dtype="auto") - ColPali
How to use 5CD-AI/ColVintern-1B-v1 with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- tokenizer_config.json +1 -0
tokenizer_config.json
CHANGED
|
@@ -119,6 +119,7 @@
|
|
| 119 |
"errors": "replace",
|
| 120 |
"model_max_length": 4096,
|
| 121 |
"pad_token": "<|endoftext|>",
|
|
|
|
| 122 |
"split_special_tokens": false,
|
| 123 |
"tokenizer_class": "Qwen2Tokenizer",
|
| 124 |
"unk_token": null
|
|
|
|
| 119 |
"errors": "replace",
|
| 120 |
"model_max_length": 4096,
|
| 121 |
"pad_token": "<|endoftext|>",
|
| 122 |
+
"processor_class": "ColInternVL2Processor",
|
| 123 |
"split_special_tokens": false,
|
| 124 |
"tokenizer_class": "Qwen2Tokenizer",
|
| 125 |
"unk_token": null
|