Instructions to use hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration") model = AutoModelForSeq2SeqLM.from_pretrained("hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 235 Bytes
-
https://huggingface.co/hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration/resolve/main/generation_config.json
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/hf-tiny-model-private/tiny-random-FSMTForConditionalGeneration/resolve/main/generation_config.json
235 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 0, | |
| "decoder_start_token_id": 2, | |
| "eos_token_id": 2, | |
| "forced_eos_token_id": 2, | |
| "max_length": 200, | |
| "num_beams": 5, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.28.0.dev0" | |
| } | |