Text Classification
Transformers
Safetensors
modernbert
agent-safety
tool-calling
long-context
distillation
Eval Results (legacy)
text-embeddings-inference
Instructions to use ProCreations/auto-200m-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProCreations/auto-200m-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ProCreations/auto-200m-2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ProCreations/auto-200m-2") model = AutoModelForSequenceClassification.from_pretrained("ProCreations/auto-200m-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from ProCreations/auto-200m-2: direct link, hf CLI and curl.
- Browser
- Download file 310 Bytes
-
https://huggingface.co/ProCreations/auto-200m-2/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://ProCreations/auto-200m-2/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/ProCreations/auto-200m-2/resolve/main/tokenizer_config.json
310 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 65536, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "unk_token": "[UNK]" | |
| } | |