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README.md

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+---
+language:
+- en
+- es
+license: apache-2.0
+tags:
+- hqq
+pipeline_tag: text-generation
+---
+
+![image/png](https://huggingface.co/datasets/malteos/images/resolve/main/occiglot.medium.png)
+
+# Occiglot-7B-ES-EN-Instruct
+
+> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
+> 
+
+**Occiglot-7B-ES-EN-Instruct** is a the instruct version of [occiglot-7b-es-en](https://huggingface.co/occiglot/occiglot-7b-es-en), a generative language model with 7B parameters supporting the Spanish and English and trained by the [Occiglot Research Collective](https://occiglot.github.io/occiglot/).
+It was trained on 160M tokens of additional multilingual and code instructions.
+Note that the model was not safety aligned and might generate problematic outputs.
+
+This is the first release of an ongoing open research project for multilingual language models. 
+If you want to train a model for your own language or are working on evaluations, please contact us or join our [Discord server](https://discord.gg/wUpvYs4XvM). **We are open for collaborations!**
+
+
+### Model details
+
+- **Instruction tuned from:** [occiglot-7b-es-en](https://huggingface.co/occiglot/occiglot-7b-es-en)
+- **Model type:** Causal decoder-only transformer language model
+- **Languages:** English, Spanish, and code.
+- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
+- **Compute resources:** [DFKI cluster](https://www.dfki.de/en/web)
+- **Contributors:** Manuel Brack, Patrick Schramowski, Pedro Ortiz, Malte Ostendorff, Fabio Barth, Georg Rehm, Kristian Kersting
+- **Research labs:** [Occiglot](https://occiglot.github.io/occiglot/) with support from [SAINT](https://www.dfki.de/en/web/research/research-departments/foundations-of-systems-ai) and [SLT](https://www.dfki.de/en/web/research/research-departments/speech-and-language-technology)
+- **Contact:** [Discord](https://discord.gg/wUpvYs4XvM)
+
+### How to use
+
+The model was trained using the chatml instruction template. You can use the transformers chat template feature for interaction.
+Since the generation relies on some randomness, we
+set a seed for reproducibility:
+
+```python
+>>> from transformers import AutoTokenizer, MistralForCausalLM, set_seed
+>>> tokenizer = AutoTokenizer.from_pretrained("occiglot/occiglot-7b-es-en-instruct")
+>>> model = MistralForCausalLM.from_pretrained('occiglot/occiglot-7b-es-en-instruct')  # You may want to use bfloat16 and/or move to GPU here
+>>> set_seed(42)
+>>> messages = [
+>>>    {"role": "system", 'content': 'You are a helpful assistant. Please give short and concise answers.'},
+>>>    {"role": "user", "content": "¿quién es el presidente del gobierno español?"},
+>>> ]
+>>> tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_dict=False, return_tensors='pt',)
+>>> set_seed(42)
+>>> outputs = model.generate(tokenized_chat.to('cuda'), max_new_tokens=200,)
+>>> tokenizer.decode(out[0][len(tokenized_chat[0]):])
+'Actualmente el presidente del gobierno español es Pedro Sánchez Pérez-Castejón'
+```
+
+## Dataset
+
+The training data was split evenly amongst Spanish and English based on the total number of tokens.
+
+**English and Code**
+ - [Open-Hermes-2B](https://huggingface.co/datasets/teknium/OpenHermes-2.5)
+
+
+**Spanish**
+ - [Mentor-ES](https://huggingface.co/datasets/projecte-aina/MentorES)
+ - [Squad-es](https://huggingface.co/datasets/squad_es)
+ - [OASST-2](https://huggingface.co/datasets/OpenAssistant/oasst2) (Spanish subset)
+ - [Aya-Dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) (Spanish subset)
+
+## Training settings
+
+- Full instruction fine-tuning on 8xH100.
+- 0.6 - 4 training epochs (depending on dataset sampling).
+- Framework: [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
+- Precision: bf16
+- Optimizer: AdamW
+- Global batch size: 128 (with 8192 context length)
+- Cosine Annealing with Warmup
+
+
+## Tokenizer
+
+Tokenizer is unchanged from [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
+
+## Evaluation
+
+Preliminary evaluation results can be found below. 
+Please note that the non-English results are based on partially machine-translated datasets and English prompts ([Belebele](https://huggingface.co/datasets/facebook/belebele) and [Okapi framework](https://github.com/nlp-uoregon/Okapi)) and thus should be interpreted with caution, e.g., biased towards English model performance.
+Currently, we are working on more suitable benchmarks for Spanish, French, German, and Italian.
+
+<details>
+<summary>Evaluation results</summary>
+  
+### All 5 Languages
+
+|                            |      avg |   arc_challenge |   belebele |   hellaswag |     mmlu |   truthfulqa |
+|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
+| Occiglot-7b-eu5            | 0.516895 |        0.508109 |   0.675556 |    0.718963 | 0.402064 |     0.279782 |
+| Occiglot-7b-eu5-instruct   | 0.537799 |        0.53632  |   0.691111 |    0.731918 | 0.405198 |     0.32445  |
+| Occiglot-7b-es-en          | 0.483388 |        0.482949 |   0.606889 |    0.653902 | 0.398922 |     0.274277 |
+| Occiglot-7b-es-en-instruct | 0.504023 |        0.494576 |   0.65     |    0.670847 | 0.406176 |     0.298513 |
+| Lince-mistral-7b-it-es     | 0.543427 |        0.540222 |   0.745111 |    0.692931 | 0.426241 |     0.312629 |
+| Mistral-7b-v0.1            | 0.547111 |        0.528937 |   0.768444 |    0.682516 | 0.448253 |     0.307403 |
+| Mistral-7b-instruct-v0.2   | 0.56713  |        0.547228 |   0.741111 |    0.69455  | 0.422501 |     0.430262 |
+
+
+### English
+
+|                            |      avg |   arc_challenge |   belebele |   hellaswag |     mmlu |   truthfulqa |
+|:---------------------------|---------:|----------------:|-----------:|------------:|---------:|-------------:|
+| Occiglot-7b-eu5            | 0.59657  |        0.530717 |   0.726667 |    0.789882 | 0.531904 |     0.403678 |
+| Occiglot-7b-eu5-instruct   | 0.617905 |        0.558874 |   0.746667 |    0.799841 | 0.535109 |     0.449    |
+| Occiglot-7b-es-en          | 0.593609 |        0.543515 |   0.697778 |    0.788289 | 0.548355 |     0.390109 |
+| Occiglot-7b-es-en-instruct | 0.615707 |        0.552048 |   0.736667 |    0.797451 | 0.557328 |     0.435042 |
+| Leo-mistral-hessianai-7b   | 0.600949 |        0.522184 |   0.736667 |    0.777833 | 0.538812 |     0.429248 |
+| Mistral-7b-v0.1            | 0.668385 |        0.612628 |   0.844444 |    0.834097 | 0.624555 |     0.426201 |
+| Mistral-7b-instruct-v0.2   | 0.713657 |        0.637372 |   0.824444 |    0.846345 | 0.59201  |     0.668116 |
+
+### Spanish
+
+|                            |      avg |   arc_challenge_es |   belebele_es |   hellaswag_es |   mmlu_es |   truthfulqa_es |
+|:---------------------------|---------:|-------------------:|--------------:|---------------:|----------:|----------------:|
+| Occiglot-7b-eu5            | 0.533194 |           0.508547 |      0.676667 |       0.725411 |  0.499325 |        0.25602  |
+| Occiglot-7b-eu5-instruct   | 0.548155 |           0.535043 |      0.68     |       0.737039 |  0.503525 |        0.285171 |
+| Occiglot-7b-es-en          | 0.527264 |           0.529915 |      0.627778 |       0.72253  |  0.512749 |        0.243346 |
+| Occiglot-7b-es-en-instruct | 0.5396   |           0.545299 |      0.636667 |       0.734372 |  0.524374 |        0.257288 |
+| Lince-mistral-7b-it-es     | 0.547212 |           0.52906  |      0.721111 |       0.687967 |  0.512749 |        0.285171 |
+| Mistral-7b-v0.1            | 0.554817 |           0.528205 |      0.747778 |       0.672712 |  0.544023 |        0.281369 |
+| Mistral-7b-instruct-v0.2   | 0.568575 |           0.54188  |      0.73     |       0.685406 |  0.511699 |        0.373891 |
+
+</details>
+
+## Acknowledgements
+
+The pre-trained model training was supported by a compute grant at the [42 supercomputer](https://hessian.ai/) which is a central component in the development of [hessian AI](https://hessian.ai/), the [AI Innovation Lab](https://hessian.ai/infrastructure/ai-innovationlab/) (funded by the [Hessian Ministry of Higher Education, Research and the Art (HMWK)](https://wissenschaft.hessen.de) & the [Hessian Ministry of the Interior, for Security and Homeland Security (HMinD)](https://innen.hessen.de)) and the [AI Service Centers](https://hessian.ai/infrastructure/ai-service-centre/) (funded by the [German Federal Ministry for Economic Affairs and Climate Action (BMWK)](https://www.bmwk.de/Navigation/EN/Home/home.html)).
+The curation of the training data is partially funded by the [German Federal Ministry for Economic Affairs and Climate Action (BMWK)](https://www.bmwk.de/Navigation/EN/Home/home.html)
+through the project [OpenGPT-X](https://opengpt-x.de/en/) (project no. 68GX21007D).
+
+
+## License
+
+[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
+
+## See also
+
+- https://huggingface.co/collections/occiglot/occiglot-eu5-7b-v01-65dbed502a6348b052695e01
+- https://huggingface.co/NikolayKozloff/occiglot-7b-es-en-GGUF

added_tokens.json

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+{
+  "<|im_end|>": 32001,
+  "<|im_start|>": 32000
+}

config.json

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+{
+  "_name_or_path": "./mayflowergmbh/occiglot-7b-es-en-instruct-hf",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.40.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32002
+}

qmodel.pt

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+size 2597218112

special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+}

tokenizer.model

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tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "<s>",
+      "lstrip": false,
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+      "single_word": false,
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+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{{'<s>'}}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful assistant. Please give a long and detailed answer.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'<|im_start|>system\n' + system_message + '<|im_end|>\n'}}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}