diff --git a/candle-pyo3/Cargo.toml b/candle-pyo3/Cargo.toml
index 75a52b4d..fd2890f6 100644
--- a/candle-pyo3/Cargo.toml
+++ b/candle-pyo3/Cargo.toml
@@ -17,3 +17,4 @@ crate-type = ["cdylib"]
 [dependencies]
 candle = { path = "../candle-core", default-features=false }
 pyo3 = { version = "0.19.0", features = ["extension-module"] }
+half = { version = "2.3.1", features = ["num-traits"] }
diff --git a/candle-pyo3/src/lib.rs b/candle-pyo3/src/lib.rs
index ab280a63..ddf7b554 100644
--- a/candle-pyo3/src/lib.rs
+++ b/candle-pyo3/src/lib.rs
@@ -1,8 +1,10 @@
-use pyo3::types::PyTuple;
 use pyo3::exceptions::{PyTypeError, PyValueError};
 use pyo3::prelude::*;
+use pyo3::types::{PyString, PyTuple};
 
-use ::candle::{Device::Cpu, Tensor};
+use half::{bf16, f16};
+
+use ::candle::{DType, Device::Cpu, Tensor};
 
 pub fn wrap_err(err: ::candle::Error) -> PyErr {
     PyErr::new::<PyValueError, _>(format!("{err:?}"))
@@ -23,15 +25,48 @@ impl std::ops::Deref for PyTensor {
 #[pymethods]
 impl PyTensor {
     #[new]
+    // TODO: Handle arbitrary input dtype and shape.
     fn new(f: f32) -> PyResult<Self> {
         Ok(Self(Tensor::new(f, &Cpu).map_err(wrap_err)?))
     }
 
+    fn values(&self, py: Python<'_>) -> PyResult<PyObject> {
+        // TODO: Handle arbitrary shapes.
+        let v = match self.0.dtype() {
+            // TODO: Use the map bits to avoid enumerating the types.
+            DType::U8 => self.to_scalar::<u8>().map_err(wrap_err)?.to_object(py),
+            DType::U32 => self.to_scalar::<u32>().map_err(wrap_err)?.to_object(py),
+            DType::F32 => self.to_scalar::<f32>().map_err(wrap_err)?.to_object(py),
+            DType::F64 => self.to_scalar::<f64>().map_err(wrap_err)?.to_object(py),
+            DType::BF16 => self
+                .to_scalar::<bf16>()
+                .map_err(wrap_err)?
+                .to_f32()
+                .to_object(py),
+            DType::F16 => self
+                .to_scalar::<f16>()
+                .map_err(wrap_err)?
+                .to_f32()
+                .to_object(py),
+        };
+        Ok(v)
+    }
+
     #[getter]
     fn shape(&self, py: Python<'_>) -> PyObject {
         PyTuple::new(py, self.0.dims()).to_object(py)
     }
 
+    #[getter]
+    fn stride(&self, py: Python<'_>) -> PyObject {
+        PyTuple::new(py, self.0.stride()).to_object(py)
+    }
+
+    #[getter]
+    fn dtype(&self, py: Python<'_>) -> PyObject {
+        PyString::new(py, self.0.dtype().as_str()).to_object(py)
+    }
+
     #[getter]
     fn rank(&self) -> usize {
         self.0.rank()
@@ -59,6 +94,21 @@ impl PyTensor {
     fn __radd__(&self, rhs: &PyAny) -> PyResult<Self> {
         self.__add__(rhs)
     }
+
+    fn __mul__(&self, rhs: &PyAny) -> PyResult<Self> {
+        let tensor = if let Ok(rhs) = rhs.extract::<Self>() {
+            (&self.0 * &rhs.0).map_err(wrap_err)?
+        } else if let Ok(rhs) = rhs.extract::<f64>() {
+            (&self.0 * rhs).map_err(wrap_err)?
+        } else {
+            Err(PyTypeError::new_err("unsupported for mul"))?
+        };
+        Ok(Self(tensor))
+    }
+
+    fn __rmul__(&self, rhs: &PyAny) -> PyResult<Self> {
+        self.__mul__(rhs)
+    }
 }
 
 #[pyfunction]