Instructions to use hf-tiny-model-private/tiny-random-EsmModel 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-EsmModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-EsmModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-EsmModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-EsmModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 275 Bytes
15fe870 | 1 2 3 4 5 6 7 | {
"clean_up_tokenization_spaces": true,
"model_max_length": 512,
"special_tokens_map_file": "/home/runner/.cache/huggingface/hub/models--facebook--esm-1b/snapshots/9d4d0ba06814338846762f17500f13bd17c1f8ce/special_tokens_map.json",
"tokenizer_class": "EsmTokenizer"
}
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