diff --git a/jax/_src/numpy/lax_numpy.py b/jax/_src/numpy/lax_numpy.py
index 6c6cacef673e..ef6a30400d30 100644
--- a/jax/_src/numpy/lax_numpy.py
+++ b/jax/_src/numpy/lax_numpy.py
@@ -5194,9 +5194,50 @@ def array_equiv(a1: ArrayLike, a2: ArrayLike) -> Array:
 
 # General np.from* style functions mostly delegate to numpy.
 
-@util.implements(np.frombuffer)
 def frombuffer(buffer: bytes | Any, dtype: DTypeLike = float,
                count: int = -1, offset: int = 0) -> Array:
+  r"""Convert a buffer into a 1-D JAX array.
+
+  JAX implementation of :func:`numpy.frombuffer`.
+
+  Args:
+    buffer: an object containing the data. It must be either a bytes object with
+      a length that is an integer multiple of the dtype element size, or
+      it must be an object exporting the `Python buffer interface`_.
+    dtype: optional. Desired data type for the array. Default is ``float64``.
+      This specifes the dtype used to parse the buffer, but note that after parsing,
+      64-bit values will be cast to 32-bit JAX arrays if the ``jax_enable_x64``
+      flag is set to ``False``.
+    count: optional integer specifying the number of items to read from the buffer.
+      If -1 (default), all items from the buffer are read.
+    offset: optional integer specifying the number of bytes to skip at the beginning
+      of the buffer. Default is 0.
+
+  Returns:
+    A 1-D JAX array representing the interpreted data from the buffer.
+
+  See also:
+    - :func:`jax.numpy.fromstring`: convert a string of text into 1-D JAX array.
+
+  Examples:
+    Using a bytes buffer:
+
+    >>> buf = b"\x00\x01\x02\x03\x04"
+    >>> jnp.frombuffer(buf, dtype=jnp.uint8)
+    Array([0, 1, 2, 3, 4], dtype=uint8)
+    >>> jnp.frombuffer(buf, dtype=jnp.uint8, offset=1)
+    Array([1, 2, 3, 4], dtype=uint8)
+
+    Constructing a JAX array via the Python buffer interface, using Python's
+    built-in :mod:`array` module.
+
+    >>> from array import array
+    >>> pybuffer = array('i', [0, 1, 2, 3, 4])
+    >>> jnp.frombuffer(pybuffer, dtype=jnp.int32)
+    Array([0, 1, 2, 3, 4], dtype=int32)
+
+  .. _Python buffer interface: https://docs.python.org/3/c-api/buffer.html
+  """
   return asarray(np.frombuffer(buffer=buffer, dtype=dtype, count=count, offset=offset))