Fill-Mask
Transformers
Safetensors
nucengram
feature-extraction
biology
genomics
dna
masked-lm
custom_code
Instructions to use FreakingPotato/NucEngram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FreakingPotato/NucEngram with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="FreakingPotato/NucEngram", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FreakingPotato/NucEngram", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,076 Bytes
cb634e7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | {
"model_type": "nucengram",
"architectures": [
"NucEngramModel"
],
"auto_map": {
"AutoConfig": "configuration_nucengram.NucEngramConfig",
"AutoModel": "modeling_nucengram.NucEngramModel",
"AutoModelForMaskedLM": "modeling_nucengram.NucEngramForMaskedLM"
},
"backbone": {
"vocab_size": 9,
"hidden_size": 512,
"intermediate_size": 2048,
"num_hidden_layers": 22,
"num_attention_heads": 16,
"max_position_embeddings": 8192,
"local_attention": 128,
"rope_theta_global": 160000.0,
"rope_theta_local": 10000.0,
"attn_implementation": "sdpa",
"tie_word_embeddings": true
},
"engram": {
"ngram_orders": [
3,
4,
5,
6,
8
],
"n_heads_per_order": 4,
"d_mem": 48,
"layer_inject_ids": [
1,
4
],
"use_conv": true,
"gate_temp": 1.0,
"seed": 0,
"hidden_size": 512,
"vocab_size": 9,
"pad_id": 0
},
"max_length": 8192,
"pad_token_id": 0,
"hidden_size": 512,
"torch_dtype": "float32",
"transformers_version": "5.7.0"
} |