requirements : update transformers/torch for Embedding Gemma (#15828)

* requirements : update transformers/torch for Embedding Gemma

This commit updates the requirements to support converting
Embedding Gemma 300m models.

The motivation for this change is that during development I had a local
copy of the transformers package which is what I used for converting
the models. This was a mistake on my part and I should have also updated
my transformers version to the official release.

I had checked the requirements/requirements-convert_legacy_llama.txt
file and noted that the version was >=4.45.1,<5.0.0 and came to the
conculusion that no updated would be needed, this assumed that
Embedding Gemma would be in a transformers release at the time
Commit fb15d649ed ("llama : add support
for EmbeddingGemma 300m (#15798)) was merged. So anyone wanting to
convert themselves would be able to do so. However, Embedding Gemma is
a preview release and this commit updates the requirements to use this
preview release.

* resolve additional python dependencies

* fix pyright errors in tokenizer test and remove unused import

tests/test-tokenizer-random.py

@@ -421,10 +421,10 @@ def compare_tokenizers(tokenizer1: TokenizerGroundtruth, tokenizer2: TokenizerLl
         if text1 == text2:  # equal to TokenizerGroundtruth?
             return True
         # equal to source text?
-        if tokenizer1.add_bos_token:  # remove BOS
+        if tokenizer1.add_bos_token and tokenizer1.bos_token and isinstance(tokenizer1.bos_token, str):  # remove BOS
             if text2.startswith(tokenizer1.bos_token):
                 text2 = text2[len(tokenizer1.bos_token):]
-        if tokenizer1.add_eos_token:  # remove EOS
+        if tokenizer1.add_eos_token and tokenizer1.eos_token and isinstance(tokenizer1.eos_token, str):  # remove EOS
             if text2.endswith(tokenizer1.eos_token):
                 text2 = text2[:-len(tokenizer1.eos_token)]
         return text == text2