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| 1 | +<!--Copyright 2025 The HuggingFace Team and the Swiss AI Initiative. All rights reserved. |
| 2 | +
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| 3 | +Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with |
| 4 | +the License. You may obtain a copy of the License at |
| 5 | +
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| 6 | +http://www.apache.org/licenses/LICENSE-2.0 |
| 7 | +
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| 8 | +Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on |
| 9 | +an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the |
| 10 | +specific language governing permissions and limitations under the License. |
| 11 | +
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| 12 | +⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be |
| 13 | +rendered properly in your Markdown viewer. |
| 14 | +
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| 15 | +--> |
| 16 | + |
| 17 | +<div style="float: right;"> |
| 18 | + <div class="flex flex-wrap space-x-1"> |
| 19 | + <img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white"> |
| 20 | + <img alt="FlashAttention" src="https://img.shields.io/badge/%E2%9A%A1%EF%B8%8E%20FlashAttention-eae0c8?style=flat"> |
| 21 | + <img alt="SDPA" src="https://img.shields.io/badge/SDPA-DE3412?style=flat&logo=pytorch&logoColor=white"> |
| 22 | + <img alt="Tensor parallelism" src="https://img.shields.io/badge/Tensor%20parallelism-06b6d4?style=flat&logoColor=white"> |
| 23 | + </div> |
| 24 | +</div> |
| 25 | + |
| 26 | +# Apertus |
| 27 | + |
| 28 | +[Apertus](https://www.swiss-ai.org) is a family of large language models from the Swiss AI Initiative. |
| 29 | + |
| 30 | +> [!TIP] |
| 31 | +> Coming soon |
| 32 | +
|
| 33 | +The example below demonstrates how to generate text with [`Pipeline`] or the [`AutoModel`], and from the command line. |
| 34 | + |
| 35 | +<hfoptions id="usage"> |
| 36 | +<hfoption id="Pipeline"> |
| 37 | + |
| 38 | +```py |
| 39 | +import torch |
| 40 | +from transformers import pipeline |
| 41 | + |
| 42 | +pipeline = pipeline( |
| 43 | + task="text-generation", |
| 44 | + model="swiss-ai/Apertus-8B", |
| 45 | + torch_dtype=torch.bfloat16, |
| 46 | + device=0 |
| 47 | +) |
| 48 | +pipeline("Plants create energy through a process known as") |
| 49 | +``` |
| 50 | + |
| 51 | +</hfoption> |
| 52 | +<hfoption id="AutoModel"> |
| 53 | + |
| 54 | +```py |
| 55 | +import torch |
| 56 | +from transformers import AutoModelForCausalLM, AutoTokenizer |
| 57 | + |
| 58 | +tokenizer = AutoTokenizer.from_pretrained( |
| 59 | + "swiss-ai/Apertus-8B", |
| 60 | +) |
| 61 | +model = AutoModelForCausalLM.from_pretrained( |
| 62 | + "swiss-ai/Apertus-8B", |
| 63 | + torch_dtype=torch.bfloat16, |
| 64 | + device_map="auto", |
| 65 | + attn_implementation="sdpa" |
| 66 | +) |
| 67 | +input_ids = tokenizer("Plants create energy through a process known as", return_tensors="pt").to("cuda") |
| 68 | + |
| 69 | +output = model.generate(**input_ids, cache_implementation="static") |
| 70 | +print(tokenizer.decode(output[0], skip_special_tokens=True)) |
| 71 | +``` |
| 72 | + |
| 73 | +</hfoption> |
| 74 | +<hfoption id="transformers CLI"> |
| 75 | + |
| 76 | +```bash |
| 77 | +echo -e "Plants create energy through a process known as" | transformers run --task text-generation --model swiss-ai/Apertus-8B --device 0 |
| 78 | +``` |
| 79 | + |
| 80 | +</hfoption> |
| 81 | +</hfoptions> |
| 82 | + |
| 83 | +## ApertusConfig |
| 84 | + |
| 85 | +[[autodoc]] ApertusConfig |
| 86 | + |
| 87 | +## ApertusModel |
| 88 | + |
| 89 | +[[autodoc]] ApertusModel |
| 90 | + - forward |
| 91 | + |
| 92 | +## ApertusForCausalLM |
| 93 | + |
| 94 | +[[autodoc]] ApertusForCausalLM |
| 95 | + - forward |
| 96 | + |
| 97 | +## ApertusForTokenClassification |
| 98 | + |
| 99 | +[[autodoc]] ApertusForTokenClassification |
| 100 | + - forward |
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