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Delete deprecated stuff (#38838)

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* delete deprecated stuff

* fix copies

* remove unused tests

* fix modernbert and fuyu

* Update src/transformers/cache_utils.py

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* bye bye `seen_tokens`

* address comments

* update typings

* ecnoder decoder models follow same pattern as whisper

* fix copies

* why is it set to False?

* fix switch transformers

* fix encoder decoder models shared weight

* fix copies and RAG

* remove `next_cache`

* fix gptj/git

* fix copies

* fix copies

* style...

* another forgotten docsrting

---------

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
This commit is contained in:
Raushan Turganbay
2025-07-10 10:18:44 +05:00
committed by GitHub
parent c6ee0b1da8
commit bc161d5d06
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docs/source/en/cache_explanation.md
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@@ -99,8 +99,6 @@ self.value_cache[layer_idx] = torch.cat([self.value_cache[layer_idx], value_stat
2. The cache grows dynamically as more tokens are processed. The sequence length dimension (`seq_len`) increases with each new token.
3. The cache maintains a count of seen tokens through `self._seen_tokens`. This is updated when the first layer processes a new token.
The example below demonstrates how to create a generation loop with [`DynamicCache`]. As discussed, the attention mask is a concatenation of past and current token values and `1` is added to the cache position for the next token.
```py