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Aira_emissions.csv

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+2023-10-06T21:09:06,Aira_emissions,a48228c1-3714-4a43-845b-663f0fe0f1a2,30336.614528894424,1.693356826881869,5.581891233344491e-05,42.5,348.0875320025388,31.305264472961426,0.3581399520067705,2.84854629411299,0.2637552799007474,3.470441526020509,Singapore,SGP,,,,Linux-5.15.120+-x86_64-with-glibc2.35,3.10.12,2.3.1,12,Intel(R) Xeon(R) CPU @ 2.20GHz,1,1 x NVIDIA A100-SXM4-40GB,103.8547,1.2929,83.48070526123047,machine,N,1.0

LICENSE

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+      You may add Your own copyright statement to Your modifications and
+      may provide additional or different license terms and conditions
+      for use, reproduction, or distribution of Your modifications, or
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+      reproduction, and distribution of the Work otherwise complies with
+      the conditions stated in this License.
+
+   5. Submission of Contributions. Unless You explicitly state otherwise,
+      any Contribution intentionally submitted for inclusion in the Work
+      by You to the Licensor shall be under the terms and conditions of
+      this License, without any additional terms or conditions.
+      Notwithstanding the above, nothing herein shall supersede or modify
+      the terms of any separate license agreement you may have executed
+      with Licensor regarding such Contributions.
+
+   6. Trademarks. This License does not grant permission to use the trade
+      names, trademarks, service marks, or product names of the Licensor,
+      except as required for reasonable and customary use in describing the
+      origin of the Work and reproducing the content of the NOTICE file.
+
+   7. Disclaimer of Warranty. Unless required by applicable law or
+      agreed to in writing, Licensor provides the Work (and each
+      Contributor provides its Contributions) on an "AS IS" BASIS,
+      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+      implied, including, without limitation, any warranties or conditions
+      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+      PARTICULAR PURPOSE. You are solely responsible for determining the
+      appropriateness of using or redistributing the Work and assume any
+      risks associated with Your exercise of permissions under this License.
+
+   8. Limitation of Liability. In no event and under no legal theory,
+      whether in tort (including negligence), contract, or otherwise,
+      unless required by applicable law (such as deliberate and grossly
+      negligent acts) or agreed to in writing, shall any Contributor be
+      liable to You for damages, including any direct, indirect, special,
+      incidental, or consequential damages of any character arising as a
+      result of this License or out of the use or inability to use the
+      Work (including but not limited to damages for loss of goodwill,
+      work stoppage, computer failure or malfunction, or any and all
+      other commercial damages or losses), even if such Contributor
+      has been advised of the possibility of such damages.
+
+   9. Accepting Warranty or Additional Liability. While redistributing
+      the Work or Derivative Works thereof, You may choose to offer,
+      and charge a fee for, acceptance of support, warranty, indemnity,
+      or other liability obligations and/or rights consistent with this
+      License. However, in accepting such obligations, You may act only
+      on Your own behalf and on Your sole responsibility, not on behalf
+      of any other Contributor, and only if You agree to indemnify,
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+   END OF TERMS AND CONDITIONS
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+   Copyright Nicholas Kluge Corrêa
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+   limitations under the License.

README.md

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+---
+license: apache-2.0
+datasets:
+- nicholasKluge/instruct-aira-dataset
+language:
+- en
+metrics:
+- accuracy
+library_name: transformers
+tags:
+- alignment
+- instruction tuned
+- text generation
+- conversation
+- assistant
+pipeline_tag: text-generation
+widget:
+- text: "<|startofinstruction|>What is your name?<|endofinstruction|>"
+  example_title: Greetings
+- text: "<|startofinstruction|>Can you explain what is Machine Learning?<|endofinstruction|>"
+  example_title: Machine Learning
+- text: "<|startofinstruction|>Do you know anything about virtue ethics?<|endofinstruction|>"
+  example_title: Ethics
+- text: "<|startofinstruction|>How can I make my girlfriend happy?<|endofinstruction|>"
+  example_title: Advise
+inference:
+  parameters:
+    repetition_penalty: 1.2
+    temperature: 0.2
+    top_k: 30
+    top_p: 0.3
+    max_length: 200
+    length_penalty: 0.3
+    early_stopping: true
+co2_eq_emissions:
+  emissions: 1.69
+  source: CodeCarbon
+  training_type: fine-tuning
+  geographical_location: United States of America
+  hardware_used: NVIDIA A100-SXM4-40GB
+---
+# Aira-2-1B5
+
+`Aira-2-1B5` is the second version of the Aira instruction-tuned series. Aira is an instruction-tuned GPT-style model based on [GPT-2](https://huggingface.co/gpt2). The model was trained with a dataset composed of prompts and completions generated synthetically by prompting already-tuned models (ChatGPT, Llama, Open-Assistant, etc).
+
+Check our gradio-demo in [Spaces](https://huggingface.co/spaces/nicholasKluge/Aira-Demo).
+
+## Details
+
+- **Size:** 1,557,614,400 parameters
+- **Dataset:** [Instruct-Aira Dataset](https://huggingface.co/datasets/nicholasKluge/instruct-aira-dataset)
+- **Language:** English
+- **Number of Epochs:** 3
+- **Batch size:** 4
+- **Optimizer:** `torch.optim.AdamW` (warmup_steps = 1e2, learning_rate = 5e-4, epsilon = 1e-8)
+- **GPU:** 1 NVIDIA A100-SXM4-40GB
+- **Emissions:** 1.69 KgCO2 (Singapore)
+- **Total Energy Consumption:** 3.47 kWh
+
+This repository has the [notebook](AIRA_FineTuning.ipynb) used to train this model.
+
+## Usage
+
+Three special tokens are used to mark the user side of the interaction and the model's response:
+
+`<|startofinstruction|>`What is a language model?`<|endofinstruction|>`A language model is a probability distribution over a vocabulary.`<|endofcompletion|>`
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+tokenizer = AutoTokenizer.from_pretrained('nicholasKluge/Aira-2-1B5')
+aira = AutoModelForCausalLM.from_pretrained('nicholasKluge/Aira-2-1B5')
+
+aira.eval()
+aira.to(device)
+
+question =  input("Enter your question: ")
+
+inputs = tokenizer(tokenizer.bos_token + question + tokenizer.sep_token, return_tensors="pt").to(device)
+
+responses = aira.generate(**inputs,
+	bos_token_id=tokenizer.bos_token_id,
+	pad_token_id=tokenizer.pad_token_id,
+	eos_token_id=tokenizer.eos_token_id,
+	do_sample=True,
+	top_k=50,
+	max_length=500,
+	top_p=0.95,
+	temperature=0.7,
+	num_return_sequences=2)
+
+print(f"Question: 👤 {question}\n")
+
+for i, response in  enumerate(responses):
+	print(f'Response {i+1}: 🤖 {tokenizer.decode(response, skip_special_tokens=True).replace(question, "")}')
+```
+
+The model will output something like:
+
+```markdown
+>>>Question: 👤 What is the capital of Brazil?
+
+>>>Response 1: 🤖 The capital of Brazil is Brasília.
+>>>Response 2: 🤖 The capital of Brazil is Brasília.
+```
+
+## Limitations
+
+🤥 Generative models can perpetuate the generation of pseudo-informative content, that is, false information that may appear truthful.
+
+🤬 In certain types of tasks, generative models can produce harmful and discriminatory content inspired by historical stereotypes.
+
+## Evaluation
+
+| Model|Average|[ARC](https://arxiv.org/abs/1803.05457)|[HellaSwag](https://arxiv.org/abs/1905.07830)|[MMLU](https://arxiv.org/abs/2009.03300)|[TruthfulQA](https://arxiv.org/abs/2109.07958)|
+|---|---|---|---|---|---|
+| [Aira-2-1B5](https://huggingface.co/nicholasKluge/Aira-2-1B5) |34.52|28.84|42.61|**26.53**|**40.11**|
+| GPT-2-xl | **36.66** | **30.29** | **51.38** | 26.43 | 38.54 |
+
+## Cite as 🤗
+
+```latex
+
+@misc{nicholas22aira,
+  doi = {10.5281/zenodo.6989727},
+  url = {https://huggingface.co/nicholasKluge/Aira-2-1B5},
+  author = {Nicholas Kluge Corrêa},
+  title = {Aira},
+  year = {2023},
+  publisher = {HuggingFace},
+  journal = {HuggingFace repository},
+}
+
+```
+
+## License
+
+The `Aira-2-1B5` is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.

added_tokens.json

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+{
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+  "<|endofinstruction|>": 50259,
+  "<|pad|>": 50260,
+  "<|startofinstruction|>": 50257
+}

config.json

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+{
+  "_name_or_path": "gpt2-xl",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 50256,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 50256,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 1024,
+  "n_embd": 1600,
+  "n_head": 25,
+  "n_inner": null,
+  "n_layer": 48,
+  "n_positions": 1024,
+  "output_past": true,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.1,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.34.0",
+  "use_cache": true,
+  "vocab_size": 50261
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.34.0"
+}

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|startofinstruction|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|endofcompletion|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|pad|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": "<|endofinstruction|>",
+  "unk_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "bos_token": {
+    "__type": "AddedToken",
+    "content": "<|startofinstruction|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "clean_up_tokenization_spaces": true,
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "<|endofcompletion|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "errors": "replace",
+  "model_max_length": 1024,
+  "pad_token": {
+    "__type": "AddedToken",
+    "content": "<|pad|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": "<|endofinstruction|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": {
+    "__type": "AddedToken",
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

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