Instructions to use hf-internal-testing/tiny-random-EsmForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-EsmForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-EsmForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-EsmForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-EsmForMaskedLM") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_max_length": 512, | |
| "name_or_path": "facebook/esm-1b", | |
| "special_tokens_map_file": "/home/huggingface/.cache/huggingface/hub/models--facebook--esm-1b/snapshots/9d4d0ba06814338846762f17500f13bd17c1f8ce/special_tokens_map.json", | |
| "tokenizer_class": "EsmTokenizer" | |
| } | |