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Aira_emissions.csv

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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
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+
+   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,
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+   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
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+      PARTICULAR PURPOSE. You are solely responsible for determining the
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+      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
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+   Copyright Nicholas Kluge Corrêa
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README.md

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 ---
 license: apache-2.0
+datasets:
+- nicholasKluge/fine-tuning-instruct-aira
+- Dahoas/synthetic-instruct-gptj-pairwise
+- databricks/databricks-dolly-15k
+- HuggingFaceH4/instruction-dataset
+language:
+- en
+metrics:
+- bleu
+library_name: transformers
+tags:
+- alignment
+- instruction tuned
+- text generation
+- conversation
+- assistant
+pipeline_tag: text-generation
+widget:
+- text: <|startoftext|>Hello! What is your name?<|endoftext|>
+  example_title: Greetings
+- text: <|startoftext|>Can you explain what is Machine Learning?<|endoftext|>
+  example_title: Machine Learning
+- text: <|startoftext|>Do you know anything about virtue ethics?<|endoftext|>
+  example_title: Ethics
+- text: <|startoftext|>How can I make my girlfried happy?<|endoftext|>
+  example_title: Advise
+inference:
+  parameters:
+    temperature: 0.2
+    top_k: 50
+    max_length: 200
 ---
+# Aira-Instruct-1.5B
+
+`Aira-Instruct-1.5B` is a instruction-tuned GPT-style model based on [GPT-2](https://huggingface.co/gpt2). The model was trained with a dataset composed of `prompt`, `completions`, generated via the [Self-Instruct](https://github.com/yizhongw/self-instruct) framework. `Aira-Instruct-1.5B` instruction-tuning was achieved via conditional text generation.
+
+The dataset used to train this model combines the following sources of data: the [`synthetic-instruct-gptj-pairwise`](https://huggingface.co/datasets/Dahoas/synthetic-instruct-gptj-pairwise) dataset, the [`databricks_dolly_15k`](https://huggingface.co/datasets/HuggingFaceH4/databricks_dolly_15k) dataset, the [`instruction-dataset`](https://huggingface.co/datasets/HuggingFaceH4/instruction-dataset) dataset, and a subset of [Aira's](https://github.com/Nkluge-correa/Aira-EXPERT) fine-tuning dataset, focused on Q&A related to Ethics, AI, AI safety, and other related topics. The dataset is available in both Portuguese and English.
+
+Check our gradio-demo in [Spaces](https://huggingface.co/spaces/nicholasKluge/Aira-Demo).
+
+## Details
+
+- **Size:** 1,557,614,400 total parameters
+- **Dataset:** [Instruct-Aira Dataset](https://huggingface.co/datasets/nicholasKluge/fine-tuning-instruct-aira)
+- **Language:** English
+- **Number of Epochs:** 2
+- **Batch size:** 4
+- **Optimizer:** `torch.optim.AdamW` (warmup_steps = 1e2, learning_rate = 5e-4, epsilon = 1e-8)
+- **GPU:** 1 NVIDIA A100-SXM4-40GB
+- **Emissions:** 0.88 KgCO2 (United States of America)
+- **Total Energy Consumption:** 1.94 kWh
+
+| Epoch/Loss|Training|Validation|
+|---|---|---|
+| 1 |0.723266|0.636748|
+| 2 |0.488247|0.594000|
+
+This repository has the notebook used to train this model.
+
+## Usage
+
+Two special tokens are used to mark the user side of the interaction and the model's response:
+
+`<|startoftext|>`What is a language model?`<|endoftext|>`A language model is a probability distribution over a vocabulary.`<|endoftext|>`
+
+```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-Instruct-1.5B')
+aira = AutoModelForCausalLM.from_pretrained('nicholasKluge/Aira-Instruct-1.5B')
+
+aira.eval()
+aira.to(device)
+
+question =  input("Enter your question: ")
+
+inputs = tokenizer(tokenizer.bos_token + question + tokenizer.eos_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=200,
+	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: 👤 Hello! What is your name?
+
+>>>Response 1: 🤖 Hi there! I am Aira, a chatbot designed to answer questions about AI ethics and AI safety. If you need assistance navigating our conversation, please feel free to ask!
+>>>Response 2: 🤖 Hi there! My name is Aira, and I'm a chatbot designed to answer questions related to AI ethics and AI Safety. If you need assistance, feel free to ask, and I'll be happy to help you out.
+```
+
+## Limitations
+
+🤥 Generative models can perpetuate the generation of pseudo-informative content, that is, false information that may appear truthful. For example, multi-modal generative models can be used to create images with untruthful content, while language models for text generation can automate the generation of misinformation.
+
+🤬 In certain types of tasks, generative models can generate toxic and discriminatory content inspired by historical stereotypes against sensitive attributes (for example, gender, race, and religion). Unfiltered public datasets may also contain inappropriate content, such as pornography, racist images, and social stereotypes, which can contribute to unethical biases in generative models. Furthermore, when prompted with non-English languages, some generative models may perform poorly.
+
+## Cite as 🤗
+
+```latex
+
+@misc{nicholas22aira,
+  doi = {10.5281/zenodo.6989727},
+  url = {https://huggingface.co/nicholasKluge/Aira-Instruct-774M},
+  author = {Nicholas Kluge Corrêa and Carolina Del Pino},
+  title = {Aira},
+  year = {2023},
+  publisher = {HuggingFace},
+  journal = {HuggingFace repository},
+}
+
+```
+
+## License
+
+The `Aira-Instruct-1.5B` is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details.

added_tokens.json

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+{
+  "<|pad|>": 50258,
+  "<|startoftext|>": 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": "4.30.2",
+  "use_cache": true,
+  "vocab_size": 50259
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.30.2"
+}

pytorch_model.bin

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+size 6230649445

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<|startoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|pad|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "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": "<|startoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  },
+  "clean_up_tokenization_spaces": true,
+  "eos_token": {
+    "__type": "AddedToken",
+    "content": "<|endoftext|>",
+    "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
+  },
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": {
+    "__type": "AddedToken",
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
+  }
+}

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