Instructions to use cloudqi/cqi_classification_pt_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cloudqi/cqi_classification_pt_v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cloudqi/cqi_classification_pt_v0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cloudqi/cqi_classification_pt_v0") model = AutoModelForSequenceClassification.from_pretrained("cloudqi/cqi_classification_pt_v0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from cloudqi/cqi_classification_pt_v0: direct link, hf CLI and curl.
- Browser
- Download file 295 Bytes
-
https://huggingface.co/cloudqi/cqi_classification_pt_v0/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://cloudqi/cqi_classification_pt_v0/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/cloudqi/cqi_classification_pt_v0/resolve/main/tokenizer_config.json
295 Bytes
| {"normalization": false, "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 128, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "vinai/bertweet-base"} |