Converting gguf fp16 & bf16 to hf is not supported.
### System Info

```
transformers==4.42.3
torch==2.3.0
numpy==1.26.4
gguf==0.6.0
```

### Who can help?

@SunMarc 

### Information

- [ ] The official example scripts
- [X] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [X] My own task or dataset (give details below)

### Reproduction

```python
import os
from transformers import AutoModelForCausalLM

gguf_path = "path/to/llama3-8b.fp16.gguf"  # or bf16
model_id = os.path.dirname(gguf_path)
gguf_file = os.path.basename(gguf_path)

model = AutoModelForCausalLM.from_pretrained(model_id, gguf_file=gguf_file)
```

### Expected behavior

Besides quantization, only F32 is implemented. FP16 and BF16 are not yet supported.

fp16 error log:
```txt
Converting and de-quantizing GGUF tensors...:   0%|                         | 0/291 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "/data2/Penut/LLM-Backend/Testing.py", line 9, in <module>
    model = AutoModelForCausalLM.from_pretrained(model_id, gguf_file=gguf_file)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 564, in from_pretrained
    return model_class.from_pretrained(
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/modeling_utils.py", line 3583, in from_pretrained
    state_dict = load_gguf_checkpoint(gguf_path, return_tensors=True)["tensors"]
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/modeling_gguf_pytorch_utils.py", line 146, in load_gguf_checkpoint
    weights = load_dequant_gguf_tensor(shape=shape, ggml_type=tensor.tensor_type, data=tensor.data)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/integrations/ggml.py", line 507, in load_dequant_gguf_tensor
    raise NotImplementedError(
NotImplementedError: ggml_type 1 not implemented - please raise an issue on huggingface transformers: https://github.com/huggingface/transformers/issues/new/choose
```

bf16 error log:
```txt
Traceback (most recent call last):
  File "/data2/Penut/LLM-Backend/Testing.py", line 9, in <module>
    model = AutoModelForCausalLM.from_pretrained(model_id, gguf_file=gguf_file)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 524, in from_pretrained
    config, kwargs = AutoConfig.from_pretrained(
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/models/auto/configuration_auto.py", line 965, in from_pretrained
    config_dict, unused_kwargs = PretrainedConfig.get_config_dict(pretrained_model_name_or_path, **kwargs)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/configuration_utils.py", line 632, in get_config_dict
    config_dict, kwargs = cls._get_config_dict(pretrained_model_name_or_path, **kwargs)
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/configuration_utils.py", line 719, in _get_config_dict
    config_dict = load_gguf_checkpoint(resolved_config_file, return_tensors=False)["config"]
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/transformers/modeling_gguf_pytorch_utils.py", line 81, in load_gguf_checkpoint
    reader = GGUFReader(gguf_checkpoint_path)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/gguf/gguf_reader.py", line 116, in __init__
    self._build_tensors(offs, tensors_fields)
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/site-packages/gguf/gguf_reader.py", line 239, in _build_tensors
    ggml_type = GGMLQuantizationType(raw_dtype[0])
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/enum.py", line 714, in __call__
    return cls.__new__(cls, value)
           ^^^^^^^^^^^^^^^^^^^^^^^
  File "/data2/Penut/.miniconda/envs/Py311/lib/python3.11/enum.py", line 1137, in __new__
    raise ve_exc
ValueError: 30 is not a valid GGMLQuantizationType
```

I tried to add F16 to `GGML_TYPES`:
```python
GGML_TYPES = {
    "F32": 0,
    "F16": 1,
    # ...
}

def load_dequant_gguf_tensor(shape, ggml_type, data):
    if ggml_type == GGML_TYPES["F32"]:
        values = data
    elif ggml_type == GGML_TYPES["F16"]:
        values = data
    # ...
```

~~I'm not sure if this is correct, but after converting to hf, the PPL is over 1000.~~