Create README.md
Browse files
README.md
ADDED
@@ -0,0 +1,112 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
language:
|
4 |
+
- en
|
5 |
+
- it
|
6 |
+
pipeline_tag: text-generation
|
7 |
+
---
|
8 |
+
|
9 |
+
![image/png](https://huggingface.co/datasets/malteos/images/resolve/main/occiglot.medium.png)
|
10 |
+
|
11 |
+
# Occiglot-7B-it-en-Instruct
|
12 |
+
|
13 |
+
> A [polyglot](https://en.wikipedia.org/wiki/Multilingualism#In_individuals) language model for the [Occident](https://en.wikipedia.org/wiki/Occident).
|
14 |
+
>
|
15 |
+
|
16 |
+
**Occiglot-7B-EU5-Instruct** is a the instruct version of [occiglot-7b-it-en](https://huggingface.co/occiglot/occiglot-7b-it-en), a generative language model with 7B parameters supporting the top-5 EU languages (English, Spanish, French, German, and Italian) and trained by the [Occiglot Research Collective](https://occiglot.github.io/occiglot/).
|
17 |
+
It was trained on 160M tokens of additional multilingual and code instructions.
|
18 |
+
Note that the model was not safety aligned and might generate problematic outputs.
|
19 |
+
|
20 |
+
This is the first release of an ongoing open research project for multilingual language models.
|
21 |
+
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!**
|
22 |
+
|
23 |
+
|
24 |
+
### Model details
|
25 |
+
|
26 |
+
- **Instruction tuned from:** [occiglot-7b-it-en](https://huggingface.co/occiglot/occiglot-7b-it-en)
|
27 |
+
- **Model type:** Causal decoder-only transformer language model
|
28 |
+
- **Languages:** English, Italian, and code.
|
29 |
+
- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
|
30 |
+
- **Compute resources:** [DFKI cluster](https://www.dfki.de/en/web)
|
31 |
+
- **Contributors:** Manuel Brack, Patrick Schramowski, Pedro Ortiz, Malte Ostendorff, Fabio Barth, Georg Rehm, Kristian Kersting
|
32 |
+
- **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)
|
33 |
+
- **Contact:** [Discord](https://discord.gg/wUpvYs4XvM)
|
34 |
+
|
35 |
+
### How to use
|
36 |
+
|
37 |
+
The model was trained using the chatml instruction template. You can use the transformers chat template feature for interaction.
|
38 |
+
Since the generation relies on some randomness, we
|
39 |
+
set a seed for reproducibility:
|
40 |
+
|
41 |
+
```python
|
42 |
+
>>> from transformers import AutoTokenizer, MistralForCausalLM, set_seed
|
43 |
+
>>> tokenizer = AutoTokenizer.from_pretrained("occiglot/occiglot-7b-eu5-instruct")
|
44 |
+
>>> model = MistralForCausalLM.from_pretrained('occiglot/occiglot-7b-eu5-instruct') # You may want to use bfloat16 and/or move to GPU here
|
45 |
+
>>> set_seed(42)
|
46 |
+
>>> messages = [
|
47 |
+
>>> {"role": "system", 'content': 'You are a helpful assistant. Please give short and concise answers.'},
|
48 |
+
>>> {"role": "user", "content": "chi è il primo ministro italiano?"},
|
49 |
+
>>> ]
|
50 |
+
>>> tokenized_chat = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_dict=False, return_tensors='pt',)
|
51 |
+
>>> set_seed(42)
|
52 |
+
>>> outputs = model.generate(tokenized_chat.to('cuda'), max_new_tokens=200,)
|
53 |
+
>>> tokenizer.decode(out[0][len(tokenized_chat[0]):])
|
54 |
+
'Il primo ministro italiano è attualmente Giorgia Meloni, presidente di Fratelli d'Italia, un partito politico di estrema destra.'
|
55 |
+
```
|
56 |
+
|
57 |
+
## Dataset
|
58 |
+
|
59 |
+
The training data was split evenly amongst the 5 languages based on the total number of tokens. We would like to thank Disco Research and Björn Plüster for making their dataset available to us.
|
60 |
+
|
61 |
+
**English and Code**
|
62 |
+
- [Open-Hermes-2B](https://huggingface.co/datasets/teknium/OpenHermes-2.5)
|
63 |
+
|
64 |
+
**Italian**
|
65 |
+
- [Quora-IT-Baize](https://huggingface.co/datasets/andreabac3/Quora-Italian-Fauno-Baize)
|
66 |
+
- [Stackoverflow-IT-Vaize](https://huggingface.co/datasets/andreabac3/StackOverflow-Italian-Fauno-Baize)
|
67 |
+
- [Camoscio](https://huggingface.co/datasets/teelinsan/camoscio_cleaned)
|
68 |
+
- [OASST-2](https://huggingface.co/datasets/OpenAssistant/oasst2) (Italian subset)
|
69 |
+
- [Aya-Dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset) (Italian subset)
|
70 |
+
|
71 |
+
## Training settings
|
72 |
+
|
73 |
+
- Full instruction fine-tuning on 8xH100.
|
74 |
+
- 0.6 - 4 training epochs (depending on dataset sampling).
|
75 |
+
- Framework: [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl)
|
76 |
+
- Precision: bf16
|
77 |
+
- Optimizer: AdamW
|
78 |
+
- Global batch size: 128 (with 8192 context length)
|
79 |
+
- Cosine Annealing with Warmup
|
80 |
+
|
81 |
+
|
82 |
+
## Tokenizer
|
83 |
+
|
84 |
+
Tokenizer is unchanged from [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1).
|
85 |
+
|
86 |
+
## Evaluation
|
87 |
+
|
88 |
+
Preliminary evaluation results can be found below.
|
89 |
+
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.
|
90 |
+
Currently, we are working on more suitable benchmarks for Spanish, French, German, and Italian.
|
91 |
+
|
92 |
+
<details>
|
93 |
+
<summary>Evaluation results</summary>
|
94 |
+
|
95 |
+
|
96 |
+
</details>
|
97 |
+
|
98 |
+
## Acknowledgements
|
99 |
+
|
100 |
+
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)).
|
101 |
+
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)
|
102 |
+
through the project [OpenGPT-X](https://opengpt-x.de/en/) (project no. 68GX21007D).
|
103 |
+
|
104 |
+
|
105 |
+
## License
|
106 |
+
|
107 |
+
[Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
|
108 |
+
|
109 |
+
## See also
|
110 |
+
|
111 |
+
- https://huggingface.co/collections/occiglot/occiglot-eu5-7b-v01-65dbed502a6348b052695e01
|
112 |
+
|