Instructions to use nliampi/blt-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nliampi/blt-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="nliampi/blt-model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("nliampi/blt-model") model = AutoModel.from_pretrained("nliampi/blt-model") - Notebooks
- Google Colab
- Kaggle
File size: 1,195 Bytes
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"added_tokens_decoder": {
"-1": {
"content": "<|pad|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"0": {
"content": "<|unk|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<|bos|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "<|eos|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"bos_token": "<|bos|>",
"clean_up_tokenization_spaces": false,
"do_lower_case": false,
"eos_token": "<|eos|>",
"extra_special_tokens": {},
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<|pad|>",
"tokenizer_class": "BltTokenizerHF",
"unk_token": "<|unk|>",
"vocab": {
"<|bos|>": 2,
"<|eos|>": 3,
"<|pad|>": 0,
"<|unk|>": 1,
"hello": 4,
"world": 5,
"ประเทศไทย": 7,
"สวัสดี": 6
}
}
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