Instructions to use baseten/DummyGemmaTextModelForEmbedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baseten/DummyGemmaTextModelForEmbedding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="baseten/DummyGemmaTextModelForEmbedding")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("baseten/DummyGemmaTextModelForEmbedding") model = AutoModel.from_pretrained("baseten/DummyGemmaTextModelForEmbedding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 670 Bytes
0d5749f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | {
"boi_token": "<start_of_image>",
"bos_token": {
"content": "<bos>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"eoi_token": "<end_of_image>",
"eos_token": {
"content": "<end_of_turn>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"image_token": "<image_soft_token>",
"pad_token": {
"content": "<pad>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"unk_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
}
|