<!--Copyright 2025 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 contains specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.

-->
*This model was published in HF papers on 2024-08-23 and contributed to Hugging Face Transformers on 2025-02-14.*

# GraniteMoeShared

## Overview

The GraniteMoe model was proposed in [Power Scheduler: A Batch Size and Token Number Agnostic Learning Rate Scheduler](https://huggingface.co/papers/2408.13359) by Yikang Shen, Matthew Stallone, Mayank Mishra, Gaoyuan Zhang, Shawn Tan, Aditya Prasad, Adriana Meza Soria, David D. Cox and Rameswar Panda.

Additionally this class GraniteMoeSharedModel adds shared experts for Moe.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer


model_path = "ibm-research/moe-7b-1b-active-shared-experts"
tokenizer = AutoTokenizer.from_pretrained(model_path)

# drop device_map if running on CPU
model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto")
model.eval()

# change input text as desired
prompt = "Write a code to find the maximum value in a list of numbers."

# tokenize the text
input_tokens = tokenizer(prompt, return_tensors="pt").to(model.device)
# generate output tokens
output = model.generate(**input_tokens, max_new_tokens=100)
# decode output tokens into text
output = tokenizer.batch_decode(output)
# loop over the batch to print, in this example the batch size is 1
for i in output:
    print(i)
```

This HF implementation is contributed by [Mayank Mishra](https://huggingface.co/mayank-mishra), [Shawn Tan](https://huggingface.co/shawntan) and [Sukriti Sharma](https://huggingface.co/SukritiSharma).

## GraniteMoeSharedConfig

[[autodoc]] GraniteMoeSharedConfig

## GraniteMoeSharedModel

[[autodoc]] GraniteMoeSharedModel
    - forward

## GraniteMoeSharedForCausalLM

[[autodoc]] GraniteMoeSharedForCausalLM
    - forward
