Instructions to use datnguyentien204/BLIP_VietNameseFineTuningModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use datnguyentien204/BLIP_VietNameseFineTuningModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="datnguyentien204/BLIP_VietNameseFineTuningModel")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("datnguyentien204/BLIP_VietNameseFineTuningModel") model = AutoModelForVisualQuestionAnswering.from_pretrained("datnguyentien204/BLIP_VietNameseFineTuningModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json
Browse files- config.json +2 -2
config.json
CHANGED
|
@@ -15,7 +15,7 @@
|
|
| 15 |
"attention_probs_dropout_prob": 0.0,
|
| 16 |
"bad_words_ids": null,
|
| 17 |
"begin_suppress_tokens": null,
|
| 18 |
-
"bos_token_id":
|
| 19 |
"chunk_size_feed_forward": 0,
|
| 20 |
"cross_attention_hidden_size": null,
|
| 21 |
"decoder_start_token_id": null,
|
|
@@ -84,7 +84,7 @@
|
|
| 84 |
"typical_p": 1.0,
|
| 85 |
"use_bfloat16": false,
|
| 86 |
"use_cache": true,
|
| 87 |
-
"vocab_size":
|
| 88 |
},
|
| 89 |
"torch_dtype": "float32",
|
| 90 |
"transformers_version": null,
|
|
|
|
| 15 |
"attention_probs_dropout_prob": 0.0,
|
| 16 |
"bad_words_ids": null,
|
| 17 |
"begin_suppress_tokens": null,
|
| 18 |
+
"bos_token_id": 119547,
|
| 19 |
"chunk_size_feed_forward": 0,
|
| 20 |
"cross_attention_hidden_size": null,
|
| 21 |
"decoder_start_token_id": null,
|
|
|
|
| 84 |
"typical_p": 1.0,
|
| 85 |
"use_bfloat16": false,
|
| 86 |
"use_cache": true,
|
| 87 |
+
"vocab_size": 119549
|
| 88 |
},
|
| 89 |
"torch_dtype": "float32",
|
| 90 |
"transformers_version": null,
|