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
File size: 7,062 Bytes
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from __future__ import annotations
import json
import os
from pathlib import Path
from typing import Any
def require_kernels_package() -> None:
"""Fail early when the precompiled-kernel runtime is not installed."""
try:
import kernels # noqa: F401
except ImportError as error:
raise RuntimeError(
"Precompiled FlashAttention requires requirements/features/flash.in."
) from error
def _kernel_lock_path() -> Path:
"""Return the kernel lock from a Hub artifact or source checkout."""
source_path = Path(__file__).resolve()
for candidate in (
source_path.parents[1] / "kernels.lock",
source_path.parents[3] / "kernels.lock",
):
if candidate.is_file():
return candidate
raise RuntimeError(
"kernels.lock is missing from the Hugging Face artifact or source checkout."
)
def _locked_entry(lock_path: Path, repository: str) -> dict[str, Any]:
try:
lock_entries = json.loads(lock_path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError) as error:
raise RuntimeError(f"Unable to read the kernel lock: {lock_path}") from error
if not isinstance(lock_entries, list):
raise RuntimeError("kernels.lock must contain a JSON list.")
if any(not isinstance(entry, dict) for entry in lock_entries):
raise RuntimeError("Every kernels.lock entry must be a JSON object.")
matches = [entry for entry in lock_entries if entry.get("repo_id") == repository]
if len(matches) != 1:
raise RuntimeError(
f"kernels.lock must contain exactly one entry for {repository!r}; found {len(matches)}."
)
return matches[0]
def _offline_mode() -> bool:
"""Return whether Hub access was explicitly disabled for this process."""
enabled_values = {"1", "on", "true", "yes"}
return any(
os.environ.get(name, "").strip().lower() in enabled_values
for name in ("HF_HUB_OFFLINE", "TRANSFORMERS_OFFLINE")
)
def _offline_snapshot_path(repository: str, revision: str) -> Path:
"""Locate one exact, possibly sparse, kernel snapshot without using Hub APIs."""
try:
from huggingface_hub import constants
from huggingface_hub.file_download import repo_folder_name
except ImportError as error:
raise RuntimeError("Offline kernel loading requires huggingface-hub.") from error
cache_root = Path(os.environ.get("KERNELS_CACHE") or constants.HF_HUB_CACHE).resolve()
repository_root = (
cache_root / repo_folder_name(repo_id=repository, repo_type="kernel")
).resolve()
snapshot = repository_root / "snapshots" / revision
if not snapshot.is_dir():
raise RuntimeError(
f"The exact offline kernel snapshot {repository}@{revision} is not cached under "
f"{cache_root}. Run `kernels download` before enabling offline mode."
)
if repository_root not in snapshot.resolve().parents:
raise RuntimeError(f"Refusing kernel snapshot outside its cache repository: {snapshot}")
return snapshot
def _load_offline_locked_kernel(
repository: str,
revision: str,
variant_locks: dict[str, object],
) -> object:
"""Validate and import the one compatible variant from a sparse Hub snapshot."""
snapshot = _offline_snapshot_path(repository, revision)
build_root = snapshot / "build"
if not build_root.is_dir():
raise RuntimeError(f"The cached kernel snapshot has no build directory: {snapshot}")
cached_names = sorted(entry.name for entry in build_root.iterdir() if entry.is_dir())
unexpected = sorted(set(cached_names).difference(variant_locks))
if unexpected:
raise RuntimeError(
f"The cached {repository}@{revision} snapshot contains unlocked variants: "
f"{', '.join(unexpected)}"
)
try:
from kernels import get_local_kernel
from kernels.utils import validate_kernel
from kernels.variants import get_variants_local, resolve_variants
except ImportError as error:
raise RuntimeError(
"Precompiled FlashAttention requires requirements/features/flash.in."
) from error
cached_variants = get_variants_local(build_root)
parsed_names = {variant.variant_str for variant in cached_variants}
invalid = sorted(set(cached_names).difference(parsed_names))
if invalid:
raise RuntimeError(
f"The cached {repository}@{revision} snapshot contains invalid variants: "
f"{', '.join(invalid)}"
)
compatible, _ = resolve_variants(cached_variants)
if len(compatible) != 1:
names = ", ".join(variant.variant_str for variant in compatible) or "none"
raise RuntimeError(
f"Expected exactly one compatible cached variant for {repository}@{revision}; "
f"found {names}."
)
variant_name = compatible[0].variant_str
variant_lock = variant_locks.get(variant_name)
expected_hash = getattr(variant_lock, "hash", None)
if not isinstance(expected_hash, str) or not expected_hash.startswith("sha256-"):
raise RuntimeError(f"The kernel lock for {variant_name} has no valid SHA-256 digest.")
# Hash validation deliberately happens before import. This operates on the
# sparse snapshot produced by `kernels download` and avoids Hub 1.23's
# full-snapshot completeness check in offline mode.
validate_kernel(repo_path=snapshot, variant=variant_name, hash=expected_hash)
return get_local_kernel(build_root / variant_name)
def load_locked_kernel(repository: str, revision: str) -> object:
"""Download, hash-validate, then import one immutable precompiled kernel."""
require_kernels_package()
try:
from kernels import get_local_kernel, install_kernel
from kernels.lockfile import KernelLock
except ImportError as error:
raise RuntimeError(
"Precompiled FlashAttention requires requirements/features/flash.in."
) from error
lock_path = _kernel_lock_path()
kernel_lock = KernelLock.from_json(_locked_entry(lock_path, repository))
if kernel_lock.sha != revision:
raise RuntimeError(
f"The typed manifest pins {repository}@{revision}, but kernels.lock pins "
f"{kernel_lock.sha}."
)
if _offline_mode():
return _load_offline_locked_kernel(repository, revision, kernel_lock.variants)
# `install_kernel` downloads data without importing it and validates the
# selected build against the tracked variant hash. Only then is the exact
# validated path imported directly. Offline mode uses the sparse-cache
# resolver above because Hub 1.23 rejects partial snapshots as incomplete.
validated_path = install_kernel(
repository,
revision=kernel_lock.sha,
variant_locks=kernel_lock.variants,
)
return get_local_kernel(validated_path)
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