Instructions to use Synthyra/ANKH3_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ANKH3_large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/ANKH3_large", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/ANKH3_large", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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a6544c4 14e58ff a6544c4 14e58ff a6544c4 | 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 | {
"architectures": [
"FastAnkhForMaskedLM"
],
"attn_backend": "sdpa",
"auto_map": {
"AutoConfig": "modeling_ankh.FastAnkhConfig",
"AutoModel": "modeling_ankh.FastAnkhModel",
"AutoModelForMaskedLM": "modeling_ankh.FastAnkhForMaskedLM",
"AutoModelForSequenceClassification": "modeling_ankh.FastAnkhForSequenceClassification",
"AutoModelForTokenClassification": "modeling_ankh.FastAnkhForTokenClassification"
},
"d_ff": 3840,
"d_kv": 64,
"d_model": 1536,
"dense_act_fn": "silu",
"dtype": "float32",
"eos_token_id": 1,
"initializer_factor": 1.0,
"layer_norm_epsilon": 1e-06,
"model_type": "fast_ankh",
"num_heads": 16,
"num_layers": 48,
"pad_token_id": 0,
"relative_attention_max_distance": 128,
"relative_attention_num_buckets": 64,
"tie_word_embeddings": false,
"transformers_version": "4.57.6",
"vocab_size": 256
}
|