Add Falcon H1 model support

[HamzaYousLM]

This pull request adds support for the Falcon H1 model to the GPTQModel repository. The following changes have been made:

• Added the falcon_h1 definition to the gptqmodel/models/definitions folder.
• Imported the falcon_h1 model in gptqmodel/models/definitions/__init__.py.
• Included falcon_h1 in the MODEL_MAP within gptqmodel/models/auto.py.

These updates enable the integration and usage of the Falcon H1 model within the framework.

[Qubitium]

@HamzaYousLM Thanks for the PR! I just a few quick questions.

1. is falcon h1 released to the public? I want to check on the modeling.py file to see if the correct order of layer modules is set.
2. related to 1, right now gate up and down are all separate, usually gate and up are together [gate, up] and down calculations depends on the result of both gate and up where gate and up do not depend on each other.

Asking because if down calculations is dependendent on result of gate + up and gate and up are not dependedent in the modeling forward, we can make the quantization faster and more accurate by grouping gate and up together. This depends on the forwarding code of the modeling.py file for falcon h1.

For most transformer models:

[ gate, up ],
[ down ]

[Qubitium]

@HamzaYousLM If falcon h1 is like falcon e which is llama based, the layer modules should be following for faster quantization. Pleaes check.

layer_modules = [
        ["feed_forward.gate_proj", "feed_forward.up_proj"],
        ["feed_forward.down_proj"],
    ]