Instructions to use Synthyra/Profluent-E1-600M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/Profluent-E1-600M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/Profluent-E1-600M", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/Profluent-E1-600M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| """Shared attention backends, masks, and optional optimized kernels.""" | |
| from ._core import ( | |
| VALID_ATTENTION_BACKENDS, | |
| AttentionBackend, | |
| BlockMask, | |
| _ensure_flash_kernels_loaded, | |
| _get_flex_attention_fn, | |
| _get_flex_block_mask, | |
| _kernels_flash_forward, | |
| _kernels_flash_varlen_forward, | |
| _unpad_input, | |
| bool_to_additive_mask, | |
| clear_flex_attention_caches, | |
| create_block_mask, | |
| flex_attention, | |
| get_attention_mask, | |
| get_attn_implementation, | |
| index_first_axis, | |
| index_put_first_axis, | |
| kernels_flash_attention_func, | |
| pad_input, | |
| resolve_attention_backend, | |
| resolve_attention_backend_for_call, | |
| set_config_attn_implementation, | |
| warn_attention_backend_fallback, | |
| ) | |
| from .interfaces import ( | |
| FASTPLMS_ATTENTION_FUNCTIONS, | |
| FASTPLMS_ATTENTION_MASKS, | |
| FastPLMsAttentionMixin, | |
| validate_transformers_attention_interfaces, | |
| ) | |
| __all__ = [ | |
| "FASTPLMS_ATTENTION_FUNCTIONS", | |
| "FASTPLMS_ATTENTION_MASKS", | |
| "VALID_ATTENTION_BACKENDS", | |
| "AttentionBackend", | |
| "BlockMask", | |
| "FastPLMsAttentionMixin", | |
| "_ensure_flash_kernels_loaded", | |
| "_get_flex_attention_fn", | |
| "_get_flex_block_mask", | |
| "_kernels_flash_forward", | |
| "_kernels_flash_varlen_forward", | |
| "_unpad_input", | |
| "bool_to_additive_mask", | |
| "clear_flex_attention_caches", | |
| "create_block_mask", | |
| "flex_attention", | |
| "get_attention_mask", | |
| "get_attn_implementation", | |
| "index_first_axis", | |
| "index_put_first_axis", | |
| "kernels_flash_attention_func", | |
| "pad_input", | |
| "resolve_attention_backend", | |
| "resolve_attention_backend_for_call", | |
| "set_config_attn_implementation", | |
| "validate_transformers_attention_interfaces", | |
| "warn_attention_backend_fallback", | |
| ] | |