Instructions to use hf-internal-testing/tiny-random-FalconForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FalconForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-FalconForTokenClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-FalconForTokenClassification") model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-FalconForTokenClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hf-internal-testing/tiny-random-FalconForTokenClassification: direct link, hf CLI and curl.
- Browser
- Download file 2.61 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-FalconForTokenClassification/resolve/refs%2Fpr%2F11/tokenizer_config.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-FalconForTokenClassification@refs/pr/11/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/hf-internal-testing/tiny-random-FalconForTokenClassification/resolve/refs%2Fpr%2F11/tokenizer_config.json
2.61 kB
| { | |
| "add_prefix_space": false, | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": ">>TITLE<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "1": { | |
| "content": ">>ABSTRACT<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "2": { | |
| "content": ">>INTRODUCTION<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "3": { | |
| "content": ">>SUMMARY<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "4": { | |
| "content": ">>COMMENT<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "5": { | |
| "content": ">>ANSWER<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "6": { | |
| "content": ">>QUESTION<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "7": { | |
| "content": ">>DOMAIN<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "8": { | |
| "content": ">>PREFIX<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "9": { | |
| "content": ">>SUFFIX<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "10": { | |
| "content": ">>MIDDLE<<", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "11": { | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| ">>TITLE<<", | |
| ">>ABSTRACT<<", | |
| ">>INTRODUCTION<<", | |
| ">>SUMMARY<<", | |
| ">>COMMENT<<", | |
| ">>ANSWER<<", | |
| ">>QUESTION<<", | |
| ">>DOMAIN<<", | |
| ">>PREFIX<<", | |
| ">>SUFFIX<<", | |
| ">>MIDDLE<<" | |
| ], | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 512, | |
| "tokenizer_class": "PreTrainedTokenizerFast" | |
| } | |