Transformers
Safetensors
t5
text2text-generation
protein-language-model
fastplms
custom_code
text-generation-inference
Instructions to use Synthyra/ANKH2_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ANKH2_large with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Synthyra/ANKH2_large", trust_remote_code=True) model = AutoModelForSeq2SeqLM.from_pretrained("Synthyra/ANKH2_large", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "agemagician/protx-large-1gspan-partreconst-15mlmp-encl48-decl24-ramd128-ranb64-dmodel1536-silu-seq768-tpuv4", | |
| "architectures": [ | |
| "T5ForConditionalGeneration" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "modeling_fastplms.FastAnkhConfig", | |
| "AutoModel": "modeling_fastplms.FastAnkhModel", | |
| "AutoModelForMaskedLM": "modeling_fastplms.FastAnkhForMaskedLMExtension", | |
| "AutoModelForSeq2SeqLM": "modeling_fastplms.FastAnkhForConditionalGeneration", | |
| "AutoModelForSequenceClassification": "modeling_fastplms.FastAnkhForSequenceClassification", | |
| "AutoModelForTokenClassification": "modeling_fastplms.FastAnkhForTokenClassification" | |
| }, | |
| "d_ff": 3840, | |
| "d_kv": 64, | |
| "d_model": 1536, | |
| "decoder_start_token_id": 0, | |
| "dense_act_fn": "silu", | |
| "dropout_rate": 0.0, | |
| "eos_token_id": 1, | |
| "fastplms_checkpoint_hash": "ca31eec9942e836d0b557a94d3b50e642af3738627a348d6526a6968b8646f8c", | |
| "fastplms_checkpoint_repo_id": "ElnaggarLab/ankh2-ext2", | |
| "fastplms_checkpoint_revision": "aa9b9fa72288c47d9f618ce80c011e24b54e17a8", | |
| "fastplms_model_id": "ankh2_large", | |
| "fastplms_release_tool_revision": "1b9ce023f1e06571cf3e6324be0610ffa53e0a4a", | |
| "fastplms_release_tool_sha256": "1459b5d7d13d9b07bd97b3eee764f2ce73623e15e32d07ddf6825c2a9509afb9", | |
| "fastplms_runtime_bundle_sha256": "17b8f83a33e63d941e3edfb8db2d8381286046b572f94194e576ca394d997597", | |
| "fastplms_runtime_revision": "1b9ce023f1e06571cf3e6324be0610ffa53e0a4a", | |
| "fastplms_source_tree_sha256": "5eb598fd991b5447e3bb6a18c92bd2300be1d94a1e169504725bc56127c1d6bc", | |
| "fastplms_weights_revision": "aa9b9fa72288c47d9f618ce80c011e24b54e17a8", | |
| "feed_forward_proj": "gated-silu", | |
| "initializer_factor": 1.0, | |
| "is_encoder_decoder": true, | |
| "is_gated_act": true, | |
| "layer_norm_epsilon": 1e-06, | |
| "model_type": "t5", | |
| "num_decoder_layers": 24, | |
| "num_heads": 16, | |
| "num_layers": 48, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "relative_attention_max_distance": 128, | |
| "relative_attention_num_buckets": 64, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.26.1", | |
| "use_cache": true, | |
| "vocab_size": 144 | |
| } | |