convert : add image break token fallback (#22914)

convert : add image break token fallback (#22914)

* convert : add image break token fallback

This commit adds a image_break_token_id fallback for mistral where the
config contains a image_break_token_id of -1:
```console
  "vision_encoder": {
    "image_token_id": 10,
    "image_break_token_id": -1,
    ...
```
But the tokenizer.json has this token:
```console
115       "id": 12,
116       "content": "[IMG_BREAK]",
117       "single_word": false,
118       "lstrip": false,
119       "rstrip": false,
120       "normalized": false,
121       "special": true
122     },
```
If we look in convert_hf_to_gguf.py we have:
```python
        elif self.is_mistral_format:
            # hparams is already vision config here so norm_eps is only defined in global_config.
            self.hparams["norm_eps"] = self.global_config.get("norm_eps", None)
            assert self.hparams["norm_eps"] is not None, "norm_eps not found in params.json"
            if self.use_break_tok:
                self.img_break_tok_id = self.find_vparam(["image_break_token_id"])
```

The motivation for this is that currently converting this models
results in the following error:
```console
load_hparams: model size:         5131.60 MiB
load_hparams: metadata size:      0.15 MiB
clip_init: failed to load model 'models/mmproj-Mistral-Medium-3.5-128B.gguf': operator(): unable to find tensor v.token_embd.img_break

mtmd_init_from_file: error: Failed to load CLIP model from models/mmproj-Mistral-Medium-3.5-128B.gguf

Failed to load vision model from models/mmproj-Mistral-Medium-3.5-128B.gguf
```

With this fallback the model loads successfully.

Resolves: https://github.com/ggml-org/llama.cpp/issues/22901

* Revert "convert : add image break token fallback"

This reverts commit 292e40cfdf9a7553863007c018236f5f554f71d8.

* convert : add image break token fallback

This commit adds a image_break_token_id fallback for mistral where the
config contains a image_break_token_id of -1:
```console
  "vision_encoder": {
    "image_token_id": 10,
    "image_break_token_id": -1,
    ...
```
But the tokenizer.json has this token:
```console
115       "id": 12,
116       "content": "[IMG_BREAK]",
117       "single_word": false,
118       "lstrip": false,
119       "rstrip": false,
120       "normalized": false,
121       "special": true
122     },
```
If we look in convert_hf_to_gguf.py we have:
```python
        elif self.is_mistral_format:
            # hparams is already vision config here so norm_eps is only defined in global_config.
            self.hparams["norm_eps"] = self.global_config.get("norm_eps", None)
            assert self.hparams["norm_eps"] is not None, "norm_eps not found in params.json"
            if self.use_break_tok:
                self.img_break_tok_id = self.find_vparam(["image_break_token_id"])
```

The motivation for this is that currently converting this models
results in the following error:
```console
load_hparams: model size:         5131.60 MiB
load_hparams: metadata size:      0.15 MiB
clip_init: failed to load model 'models/mmproj-Mistral-Medium-3.5-128B.gguf': operator(): unable to find tensor v.token_embd.img_break

mtmd_init_from_file: error: Failed to load CLIP model from models/mmproj-Mistral-Medium-3.5-128B.gguf

Failed to load vision model from models/mmproj-Mistral-Medium-3.5-128B.gguf
```

With this fallback the model loads successfully.

Co-authored-by: Pascal <redacted>
Resolves: https://github.com/ggml-org/llama.cpp/issues/22901

* convert : allow zero value for img_break_tok_id