Fix: Correct float feature generation in `generate_examples`
This PR fixes a bug in the `generate_examples` function where `datasets.Value` features with a `float` dtype were incorrectly generated using `np.random.randint`. This resulted in integer values being cast to float, which is not representative of true floating-point data.

**Key changes include:**
1.  Added explicit handling for float features using `np.random.rand` to generate continuous values.
2.  Introduced fail-fast type checks for unsupported dtypes to improve robustness.
3.  Added validation for sequence features to ensure `seq_shapes` is provided.


### Before Fix
Float features were generated incorrectly as integers cast to float:

```text
Example 0:
int_feature: 0
float_feature: 9.0  <-- Incorrect: An integer disguised as a float
string_feature: The small grey turtle was surprisingly fast...
seq_feature: [0.3048 0.4291 0.4283]
```
### After Fix
Float features are now correctly generated as continuous numbers in the range [0, 1):
```text

Example 0:
int_feature: 0
float_feature: 0.0183  <-- Correct: A true random float
string_feature: The small grey turtle was surprisingly fast...
seq_feature: [0.9237 0.7972 0.8526]