Instructions to use Synthyra/Profluent-E1-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/Profluent-E1-150M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/Profluent-E1-150M", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/Profluent-E1-150M", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,157 Bytes
cb4264d | 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 | {
"architectures": [
"E1ForMaskedLM"
],
"attn_backend": "sdpa",
"auto_map": {
"AutoConfig": "modeling_e1.E1Config",
"AutoModel": "modeling_e1.E1Model",
"AutoModelForMaskedLM": "modeling_e1.E1ForMaskedLM",
"AutoModelForSequenceClassification": "modeling_e1.E1ForSequenceClassification",
"AutoModelForTokenClassification": "modeling_e1.E1ForTokenClassification"
},
"bos_token_id": 1,
"clip_qkv": 8,
"dtype": "bfloat16",
"eos_token_id": 2,
"gated_mlp": true,
"global_attention_every_n_layers": 3,
"gradient_checkpointing": false,
"hidden_act": "silu",
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 2304,
"max_num_positions_global": 65536,
"max_num_positions_within_seq": 8192,
"max_num_sequences": 512,
"model_type": "E1",
"no_ffn_gradient_checkpointing": true,
"num_attention_heads": 12,
"num_hidden_layers": 20,
"num_key_value_heads": 12,
"pad_token_id": 0,
"rms_norm_eps": 1e-05,
"rope_theta_global": 500000.0,
"rope_theta_within_seq": 10000.0,
"tie_word_embeddings": false,
"transformers_version": "4.57.6",
"use_cache": true,
"vocab_size": 34
}
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