build(deps): bump transformers from 4.35.0 to 4.38.2

[dependabot]

Bumps transformers from 4.35.0 to 4.38.2.

Release notes

Sourced from transformers's releases.

v4.38.2

Fix backward compatibility issues with Llama and Gemma:

We mostly made sure that performances are not affected by the new change of paradigm with ROPE. Fixed the ROPE computation (should always be in float32) and the causal_mask dtype was set to bool to take less RAM.

YOLOS had a regression, and Llama / T5Tokenizer had a warning popping for random reasons

• FIX [Gemma] Fix bad rebase with transformers main (#29170)
• Improve _update_causal_mask performance (#29210)
• [T5 and Llama Tokenizer] remove warning (#29346)
• [Llama ROPE] Fix torch export but also slow downs in forward (#29198)
• RoPE loses precision for Llama / Gemma + Gemma logits.float() (#29285)
• Patch YOLOS and others (#29353)
• Use torch.bool instead of torch.int64 for non-persistant causal mask buffer (#29241)

v4.38.1

Fix eager attention in Gemma!

• [Gemma] Fix eager attention #29187 by @​sanchit-gandhi

TLDR:

-        attn_output = attn_output.reshape(bsz, q_len, self.hidden_size)
+        attn_output = attn_output.view(bsz, q_len, -1)

v4.38: Gemma, Depth Anything, Stable LM; Static Cache, HF Quantizer, AQLM

New model additions

💎 Gemma 💎

Gemma is a new opensource Language Model series from Google AI that comes with a 2B and 7B variant. The release comes with the pre-trained and instruction fine-tuned versions and you can use them via AutoModelForCausalLM, GemmaForCausalLM or pipeline interface!

Read more about it in the Gemma release blogpost: https://hf.co/blog/gemma

from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")
model = AutoModelForCausalLM.from_pretrained("google/gemma-2b", device_map="auto", torch_dtype=torch.float16)
input_text = "Write me a poem about Machine Learning."
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**input_ids)

You can use the model with Flash Attention, SDPA, Static cache and quantization API for further optimizations !

• Flash Attention 2

... (truncated)

Commits

• 092f1fd Release 4.38.2
• bf5163f fix merge conflicts between llama and gemma
• 6c45f0f Use torch.bool instead of torch.int64 for non-persistant causal mask buff...
• bfefb8e Patch YOLOS and others (#29353)
• 20164cc RoPE loses precision for Llama / Gemma + Gemma logits.float() (#29285)
• d5ec194 [Llama ROPE] Fix torch export but also slow downs in forward (#29198)
• bf99e86 [T5 and Llama Tokenizer] remove warning (#29346)
• 6d02350 Improve _update_causal_mask performance (#29210)
• 4f8689e FIX [Gemma] Fix bad rebase with transformers main (#29170)
• a085774 Release: v4.38.1
• Additional commits viewable in compare view

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[bot-anik]

@dependabot merge

[dependabot]

One of your CI runs failed on this pull request, so Dependabot won't merge it.

Dependabot will still automatically merge this pull request if you amend it and your tests pass.

[dependabot]

Superseded by #162.