Instructions to use Rocketknight1/hyenadna-tiny-1k-seqlen-hf-finetuned-human-enhancers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rocketknight1/hyenadna-tiny-1k-seqlen-hf-finetuned-human-enhancers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Rocketknight1/hyenadna-tiny-1k-seqlen-hf-finetuned-human-enhancers", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("Rocketknight1/hyenadna-tiny-1k-seqlen-hf-finetuned-human-enhancers", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "hyenadna-tiny-1k-seqlen-hf", | |
| "activation_freq": 10, | |
| "architectures": [ | |
| "HyenaDNAForSequenceClassification" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_hyena.HyenaConfig", | |
| "AutoModel": "modeling_hyena.HyenaDNAModel", | |
| "AutoModelForCausalLM": "modeling_hyena.HyenaDNAForCausalLM", | |
| "AutoModelForSequenceClassification": "modeling_hyena.HyenaDNAForSequenceClassification" | |
| }, | |
| "d_inner": 512, | |
| "d_model": 128, | |
| "emb_dim": 5, | |
| "embed_dropout": 0.1, | |
| "filter_order": 64, | |
| "hyena_dropout": 0.0, | |
| "hyena_filter_dropout": 0.0, | |
| "hyena_order": 2, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "max_seq_len": 1026, | |
| "model_type": "hyenadna", | |
| "n_layer": 2, | |
| "num_inner_mlps": 2, | |
| "pad_token_id": 4, | |
| "pad_vocab_size_multiple": 8, | |
| "problem_type": "single_label_classification", | |
| "short_filter_order": 3, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "train_freq": true, | |
| "transformers_version": "4.37.0.dev0", | |
| "use_bias": true, | |
| "vocab_size": 12 | |
| } | |