Fix: Correct float feature generation in `generate_examples` 
Hi @lhoestq, just a gentle follow-up on this PR.
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:**

* Added explicit handling for `float` features using `np.random.rand` to generate continuous values.
* Introduced fail-fast type checks for unsupported dtypes to improve robustness.
* 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]
```
#### Note: This PR is a follow-up/fix of the previously closed PR #7769 for clarity and context.
