Instructions to use Synthyra/ESMFold2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESMFold2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/ESMFold2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Synthyra/ESMFold2", trust_remote_code=True) model = AutoModel.from_pretrained("Synthyra/ESMFold2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 12,385 Bytes
74b8b2a 80c2fed 74b8b2a 80c2fed e0ac7d5 74b8b2a 80c2fed 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 59abcec 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 59abcec 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 80c2fed 74b8b2a 80c2fed | 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 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 | """Resolve and validate Hugging Face kernels before importing their binaries."""
from __future__ import annotations
import hashlib
import json
import os
import re
from pathlib import Path
from typing import Any
# kernels.lock records, per locked build variant, one SHA-256 over the variant's relative
# file paths and the Git or Git LFS object IDs of their contents. kernels 0.17 no longer
# writes or checks these digests, so this module checks them before anything is imported.
_VARIANT_HASH_TYPE = "git_lfs_concat"
_VARIANT_DIGEST = re.compile(r"sha256-[0-9a-f]{64}")
# The Hub cache names a Git blob by its 40-character SHA-1 object ID and Git LFS content
# by its 64-character SHA-256.
_GIT_OBJECT_ID_LENGTH = 40
_LFS_OBJECT_ID_LENGTH = 64
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 _locked_variant_digests(entry: dict[str, Any]) -> dict[str, str]:
"""Each locked build variant of one kernels.lock entry, mapped to its digest."""
variants = entry.get("variants")
if not isinstance(variants, dict) or not variants:
raise RuntimeError(f"kernels.lock locks no build variants for {entry.get('repo_id')!r}.")
digests: dict[str, str] = {}
for variant_name, variant_lock in variants.items():
expected_hash = variant_lock.get("hash") if isinstance(variant_lock, dict) else None
if (
not isinstance(expected_hash, str)
or _VARIANT_DIGEST.fullmatch(expected_hash) is None
or variant_lock.get("hash_type") != _VARIANT_HASH_TYPE
):
raise RuntimeError(f"The kernel lock for {variant_name} has no valid SHA-256 digest.")
digests[variant_name] = expected_hash
return digests
def _git_blob_object_id(contents: bytes) -> bytes:
"""Return the SHA-1 object ID Git assigns to a blob with these contents."""
return hashlib.sha1(b"blob %d\0" % len(contents) + contents).digest()
def validate_variant_digest(snapshot: Path, variant_name: str, expected_hash: str) -> None:
"""Check one cached build variant against its kernels.lock digest before import.
Snapshot files link into the Hub cache's content-addressed blobs. Each linked file
contributes its path relative to the variant, then the object ID its contents hash to:
a Git blob ID when the cache names the blob by SHA-1, a Git LFS SHA-256 otherwise.
Files that are not links are skipped, because importing a kernel writes bytecode
beside it.
"""
variant_root = snapshot / "build" / variant_name
linked_files: list[tuple[bytes, Path]] = []
for directory, _, file_names in os.walk(variant_root):
for file_name in file_names:
path = Path(directory) / file_name
if path.is_symlink():
relative_name = path.relative_to(variant_root).as_posix().encode("utf-8")
linked_files.append((relative_name, path))
digest = hashlib.sha256()
for relative_name, path in sorted(linked_files):
contents = path.read_bytes()
object_id_length = len(path.resolve().name)
if object_id_length == _GIT_OBJECT_ID_LENGTH:
object_id = _git_blob_object_id(contents)
elif object_id_length == _LFS_OBJECT_ID_LENGTH:
object_id = hashlib.sha256(contents).digest()
else:
raise RuntimeError(f"Unexpected Hub cache blob name behind {path}.")
digest.update(relative_name)
digest.update(object_id)
received_hash = f"sha256-{digest.hexdigest()}"
if received_hash != expected_hash:
raise RuntimeError(
f"The cached kernel variant {variant_name} hashes to {received_hash}, but "
f"kernels.lock records {expected_hash}."
)
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}. Load the kernel once with Hub access 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_digests: dict[str, str],
) -> 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_digests))
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.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
# Hash validation deliberately happens before import. It reads the sparse snapshot
# directly, so no Hub API judges whether the snapshot is complete.
validate_variant_digest(snapshot, variant_name, variant_digests[variant_name])
return get_local_kernel(build_root / variant_name)
def _compatible_locked_variants(repository: str, variant_names: list[str]) -> list[str]:
"""Return the locked build variants `kernels` can load on this system, preferred first."""
try:
from kernels.variants import parse_variant, resolve_variants
except ImportError as error:
raise RuntimeError(
"Precompiled FlashAttention requires requirements/features/flash.in."
) from error
try:
locked_variants = [parse_variant(variant_name) for variant_name in variant_names]
except ValueError as error:
raise RuntimeError(f"kernels.lock contains an invalid {repository} variant.") from error
compatible, _ = resolve_variants(locked_variants)
return [variant.variant_str for variant in compatible]
def _preferred_locked_variant(repository: str, revision: str, variant_names: list[str]) -> str:
"""Return the locked build variant `kernels` prefers on this system."""
compatible = _compatible_locked_variants(repository, variant_names)
if not compatible:
raise RuntimeError(
f"kernels.lock locks no build of {repository}@{revision} for this system; "
f"locked variants: {', '.join(sorted(variant_names))}."
)
return compatible[0]
def _pinned_variant_digests(repository: str, revision: str) -> dict[str, str]:
"""Return the locked build digests of a kernel whose kernels.lock entry pins `revision`."""
entry = _locked_entry(_kernel_lock_path(), repository)
locked_revision = entry.get("sha")
if locked_revision != revision:
raise RuntimeError(
f"The typed manifest pins {repository}@{revision}, but kernels.lock pins "
f"{locked_revision}."
)
return _locked_variant_digests(entry)
def locked_variant_for_this_system(repository: str, revision: str) -> str | None:
"""Return the locked build `kernels` would load here, or None when kernels.lock pins none.
Only kernels.lock is read, so a caller can tell a platform the lock does not cover
apart from a download, digest, or import failure.
"""
variant_digests = _pinned_variant_digests(repository, revision)
compatible = _compatible_locked_variants(repository, list(variant_digests))
return compatible[0] if compatible else None
def load_locked_kernel(repository: str, revision: str) -> object:
"""Download, hash-validate, then import one immutable precompiled kernel."""
require_kernels_package()
try:
from huggingface_hub import snapshot_download
from kernels import get_local_kernel
except ImportError as error:
raise RuntimeError(
"Precompiled FlashAttention requires requirements/features/flash.in."
) from error
variant_digests = _pinned_variant_digests(repository, revision)
if _offline_mode():
return _load_offline_locked_kernel(repository, revision, variant_digests)
# Only a locked build can be selected, and only its files are downloaded, at the
# immutable revision. The download imports nothing; the digest check runs first.
variant_name = _preferred_locked_variant(repository, revision, list(variant_digests))
snapshot = Path(
snapshot_download(
repository,
repo_type="kernel",
revision=revision,
allow_patterns=[f"build/{variant_name}/*"],
cache_dir=os.environ.get("KERNELS_CACHE") or None,
)
)
validate_variant_digest(snapshot, variant_name, variant_digests[variant_name])
return get_local_kernel(snapshot / "build" / variant_name)
|