Instructions to use scott156/LEDBaseNSPCCV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scott156/LEDBaseNSPCCV1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("scott156/LEDBaseNSPCCV1") model = AutoModelForSeq2SeqLM.from_pretrained("scott156/LEDBaseNSPCCV1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from scott156/LEDBaseNSPCCV1: direct link, hf CLI and curl.
- Browser
- Download file 205 Bytes
-
https://huggingface.co/scott156/LEDBaseNSPCCV1/resolve/main/generation_config.json
- Command line
-
hf download hf://scott156/LEDBaseNSPCCV1/generation_config.json
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curl -L -o generation_config.json https://huggingface.co/scott156/LEDBaseNSPCCV1/resolve/main/generation_config.json
205 Bytes
| { | |
| "bos_token_id": 0, | |
| "decoder_start_token_id": 2, | |
| "eos_token_id": 2, | |
| "max_new_tokens": 400, | |
| "no_repeat_ngram_size": 5, | |
| "num_beams": 3, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.39.3" | |
| } | |