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Add the Bamba Model (#34982)

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* initial commit for PR

Co-authored-by: Gabe Goodhart <gabe.l.hart@gmail.com>

* rename dynamic cache

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* add more unit tests

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* add integration test

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* add integration test

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* Add modular bamba file

* Remove trainer changes from unrelated PR

* Modify modular and cofig to get model running

* Fix some CI errors and beam search

* Fix a plethora of bugs from CI/docs/etc

* Add bamba to models with special caches

* Updat to newer mamba PR for mamba sublayer

* fix test_left_padding_compatibility

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* fix style

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* fix remaining tests

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* missed this test

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* ran make style

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* move slow tag to integration obj

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* make style

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* address comments

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* fix modular

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* left out one part of modular

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* change model

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* Make Rotary modular as well

* Update bamba.md

Added overview, update Model inference card and added config

* Update bamba.md

* Update bamba.md

* Update bamba.md

Minor fixes

* Add docs for config and model back

Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>

* Add warning when using fast kernels

* replaced generate example

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>

* Address comments from PR

Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>

* Propagate attention fixes

Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>

* Fix attention interfaces to the new API

Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>

* Fix API for decoder layer

Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>

* Remove extra weights

Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>

---------

Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com>
Signed-off-by: Antoni Viros i Martin <aviros@ibm.com>
Co-authored-by: Gabe Goodhart <gabe.l.hart@gmail.com>
Co-authored-by: Antoni Viros i Martin <aviros@ibm.com>
Co-authored-by: divya-kumari32 <72085811+divya-kumari32@users.noreply.github.com>
Co-authored-by: Antoni Viros <ani300@gmail.com>
This commit is contained in:
Yu Chin Fabian Lim
2024-12-19 03:18:17 +08:00
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parent 9a94dfe123
commit 9613933b02
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2
docs/source/en/_toctree.yml
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@@ -322,6 +322,8 @@
sections:
- local: model_doc/albert
title: ALBERT
- local: model_doc/bamba
title: Bamba
- local: model_doc/bart
title: BART
- local: model_doc/barthez

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docs/source/en/index.md
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@@ -66,6 +66,7 @@ Flax), PyTorch, and/or TensorFlow.
| [AriaText](model_doc/aria_text) | ✅ | ❌ | ❌ |
| [Audio Spectrogram Transformer](model_doc/audio-spectrogram-transformer) | ✅ | ❌ | ❌ |
| [Autoformer](model_doc/autoformer) | ✅ | ❌ | ❌ |
| [Bamba](model_doc/bamba) | ✅ | ❌ | ❌ |
| [Bark](model_doc/bark) | ✅ | ❌ | ❌ |
| [BART](model_doc/bart) | ✅ | ✅ | ✅ |
| [BARThez](model_doc/barthez) | ✅ | ✅ | ✅ |

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docs/source/en/model_doc/bamba.md Normal file
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@@ -0,0 +1,64 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# Bamba
## Overview
Bamba-9B is a decoder-only language model based on the [Mamba-2](https://github.com/state-spaces/mamba) architecture and is designed to handle a wide range of text generation tasks. It is trained from scratch using a two-stage training approach. In the first stage, the model is trained on 2 trillion tokens from the Dolma v1.7 dataset. In the second stage, it undergoes additional training on 200 billion tokens, leveraging a carefully curated blend of high-quality data to further refine its performance and enhance output quality.
Checkout all Bamba-9B model checkpoints [here](https://github.com/foundation-model-stack/bamba).
## BambaConfig
| Model | Params | # Layers | Hidden Dim. | Attention Heads | GQA | KV Heads | Context Length | Tied Embeddings |
|-------------------|--------------|----------|-------------|-----------------|-----|----------|----------------|------------------|
| Bamba | 9B (9.78B) | 32 | 4096 | 32 | Yes | 8 | 4096 | True |
[[autodoc]] BambaConfig
<!---
## Usage Tips
Tips:
- The architecture is based on Mamba-2 models.
## BambaModel
[[autodoc]] BambaModel
- forward
-->
## BambaForCausalLM
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("ibm-fms/Bamba-9B")
tokenizer = AutoTokenizer.from_pretrained("ibm-fms/Bamba-9B")
message = ["Mamba is a snake with following properties "]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = model.generate(**inputs, max_new_tokens=64)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
```
[[autodoc]] BambaForCausalLM
- forward
This HF implementation is contributed by [ani300](https://github.com/ani300) and [fabianlim](https://github.com/fabianlim).

2
docs/source/en/perf_infer_gpu_one.md
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@@ -39,6 +39,7 @@ FlashAttention-2 is experimental and may change considerably in future versions.
FlashAttention-2 is currently supported for the following architectures:
* [Aria](https://huggingface.co/docs/transformers/model_doc/aria#transformers.AriaForConditionalGeneration)
* [Bark](https://huggingface.co/docs/transformers/model_doc/bark#transformers.BarkModel)
* [Bamba](https://huggingface.co/docs/transformers/model_doc/bamba#transformers.BambaModel)
* [Bart](https://huggingface.co/docs/transformers/model_doc/bart#transformers.BartModel)
* [Chameleon](https://huggingface.co/docs/transformers/model_doc/chameleon#transformers.Chameleon)
* [CLIP](https://huggingface.co/docs/transformers/model_doc/clip#transformers.CLIPModel)
@@ -220,6 +221,7 @@ For now, Transformers supports SDPA inference and training for the following arc
* [Albert](https://huggingface.co/docs/transformers/model_doc/albert#transformers.AlbertModel)
* [Aria](https://huggingface.co/docs/transformers/model_doc/aria#transformers.AriaForConditionalGeneration)
* [Audio Spectrogram Transformer](https://huggingface.co/docs/transformers/model_doc/audio-spectrogram-transformer#transformers.ASTModel)
* [Bamba](https://huggingface.co/docs/transformers/model_doc/bamba#transformers.BambaModel)
* [Bart](https://huggingface.co/docs/transformers/model_doc/bart#transformers.BartModel)
* [Beit](https://huggingface.co/docs/transformers/model_doc/beit#transformers.BeitModel)
* [Bert](https://huggingface.co/docs/transformers/model_doc/bert#transformers.BertModel)