Instructions to use hf-internal-testing/tiny-random-MptForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MptForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-MptForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MptForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-MptForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hf-internal-testing/tiny-random-MptForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 237 Bytes
-
https://huggingface.co/hf-internal-testing/tiny-random-MptForSequenceClassification/resolve/5fb7d4e45f52c5c67c02bd133c2ae23338dbc576/tokenizer_config.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MptForSequenceClassification@5fb7d4e45f52c5c67c02bd133c2ae23338dbc576/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/hf-internal-testing/tiny-random-MptForSequenceClassification/resolve/5fb7d4e45f52c5c67c02bd133c2ae23338dbc576/tokenizer_config.json
237 Bytes
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "model_max_length": 2048, | |
| "tokenizer_class": "GPTNeoXTokenizer", | |
| "unk_token": "<|endoftext|>" | |
| } | |