diff --git a/candle-core/src/display.rs b/candle-core/src/display.rs
index 8d1f16f6..81ca3c98 100644
--- a/candle-core/src/display.rs
+++ b/candle-core/src/display.rs
@@ -186,8 +186,8 @@ trait TensorFormatter {
                     .and_then(|t| t.to_vec1::<Self::Elem>())
                 {
                     for v in vs.into_iter() {
-                        self.fmt(v, max_w, f)?;
                         write!(f, ", ")?;
+                        self.fmt(v, max_w, f)?;
                     }
                 }
             }
@@ -257,7 +257,7 @@ struct FloatFormatter<S: WithDType> {
 
 impl<S> FloatFormatter<S>
 where
-    S: WithDType + num_traits::Float,
+    S: WithDType + num_traits::Float + std::fmt::Display,
 {
     fn new(t: &Tensor, po: &PrinterOptions) -> Result<Self> {
         let mut int_mode = true;
@@ -275,6 +275,7 @@ where
             let mut nonzero_finite_min = S::max_value();
             let mut nonzero_finite_max = S::min_value();
             for &v in values.iter() {
+                let v = v.abs();
                 if v < nonzero_finite_min {
                     nonzero_finite_min = v
                 }
@@ -289,7 +290,6 @@ where
                     break;
                 }
             }
-
             if let Some(v1) = S::from(1000.) {
                 if let Some(v2) = S::from(1e8) {
                     if let Some(v3) = S::from(1e-4) {
diff --git a/candle-core/src/tensor.rs b/candle-core/src/tensor.rs
index b64f63e1..95254bab 100644
--- a/candle-core/src/tensor.rs
+++ b/candle-core/src/tensor.rs
@@ -652,18 +652,22 @@ impl Tensor {
     }
 
     pub fn flatten(&self, start_dim: Option<usize>, end_dim: Option<usize>) -> Result<Tensor> {
-        let start_dim = start_dim.unwrap_or(0);
-        let end_dim = end_dim.unwrap_or_else(|| self.rank() - 1);
-        if start_dim < end_dim {
-            let dims = self.dims();
-            let mut dst_dims = dims[..start_dim].to_vec();
-            dst_dims.push(dims[start_dim..end_dim + 1].iter().product::<usize>());
-            if end_dim + 1 < dims.len() {
-                dst_dims.extend(&dims[end_dim + 1..]);
-            }
-            self.reshape(dst_dims)
+        if self.rank() == 0 {
+            self.reshape(1)
         } else {
-            Ok(self.clone())
+            let start_dim = start_dim.unwrap_or(0);
+            let end_dim = end_dim.unwrap_or_else(|| self.rank() - 1);
+            if start_dim < end_dim {
+                let dims = self.dims();
+                let mut dst_dims = dims[..start_dim].to_vec();
+                dst_dims.push(dims[start_dim..end_dim + 1].iter().product::<usize>());
+                if end_dim + 1 < dims.len() {
+                    dst_dims.extend(&dims[end_dim + 1..]);
+                }
+                self.reshape(dst_dims)
+            } else {
+                Ok(self.clone())
+            }
         }
     }
 
diff --git a/candle-core/tests/display_tests.rs b/candle-core/tests/display_tests.rs
new file mode 100644
index 00000000..eaa60180
--- /dev/null
+++ b/candle-core/tests/display_tests.rs
@@ -0,0 +1,84 @@
+use anyhow::Result;
+use candle::{DType, Device::Cpu, Tensor};
+
+#[test]
+fn display_scalar() -> Result<()> {
+    let t = Tensor::new(1234u32, &Cpu)?;
+    let s = format!("{t}");
+    assert_eq!(&s, "[1234]\nTensor[[], u32]");
+    let t = t.to_dtype(DType::F32)?.neg()?;
+    let s = format!("{}", (&t / 10.0)?);
+    assert_eq!(&s, "[-123.4000]\nTensor[[], f32]");
+    let s = format!("{}", (&t / 1e8)?);
+    assert_eq!(&s, "[-1.2340e-5]\nTensor[[], f32]");
+    let s = format!("{}", (&t * 1e8)?);
+    assert_eq!(&s, "[-1.2340e11]\nTensor[[], f32]");
+    let s = format!("{}", (&t * 0.)?);
+    assert_eq!(&s, "[0.]\nTensor[[], f32]");
+    Ok(())
+}
+
+#[test]
+fn display_vector() -> Result<()> {
+    let t = Tensor::new::<&[u32; 0]>(&[], &Cpu)?;
+    let s = format!("{t}");
+    assert_eq!(&s, "[]\nTensor[[0], u32]");
+    let t = Tensor::new(&[0.1234567, 1.0, -1.2, 4.1, f64::NAN], &Cpu)?;
+    let s = format!("{t}");
+    assert_eq!(
+        &s,
+        "[ 0.1235,  1.0000, -1.2000,  4.1000,     NaN]\nTensor[[5], f64]"
+    );
+    let t = (Tensor::ones(50, DType::F32, &Cpu)? * 42.)?;
+    let s = format!("\n{t}");
+    let expected = r#"
+[42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42.,
+ 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42.,
+ 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42., 42.,
+ 42., 42.]
+Tensor[[50], f32]"#;
+    assert_eq!(&s, expected);
+    let t = (Tensor::ones(11000, DType::F32, &Cpu)? * 42.)?;
+    let s = format!("{t}");
+    assert_eq!(
+        &s,
+        "[42., 42., 42., ..., 42., 42., 42.]\nTensor[[11000], f32]"
+    );
+    Ok(())
+}
+
+#[test]
+fn display_multi_dim() -> Result<()> {
+    let t = (Tensor::ones((200, 100), DType::F32, &Cpu)? * 42.)?;
+    let s = format!("\n{t}");
+    let expected = r#"
+[[42., 42., 42., ..., 42., 42., 42.],
+ [42., 42., 42., ..., 42., 42., 42.],
+ [42., 42., 42., ..., 42., 42., 42.],
+ ...
+ [42., 42., 42., ..., 42., 42., 42.],
+ [42., 42., 42., ..., 42., 42., 42.],
+ [42., 42., 42., ..., 42., 42., 42.]]
+Tensor[[200, 100], f32]"#;
+    assert_eq!(&s, expected);
+    let t = t.reshape(&[2, 1, 1, 100, 100])?;
+    let t = format!("\n{t}");
+    let expected = r#"
+[[[[[42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.],
+    ...
+    [42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.]]]],
+ [[[[42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.],
+    ...
+    [42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.],
+    [42., 42., 42., ..., 42., 42., 42.]]]]]
+Tensor[[2, 1, 1, 100, 100], f32]"#;
+    assert_eq!(&t, expected);
+    Ok(())
+}