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--- |
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base_model: mistralai/Mistral-7B-v0.1 |
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tags: |
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- mistral |
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- instruct |
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- bggpt |
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- insait |
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language: |
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- bg |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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license: apache-2.0 |
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--- |
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# INSAIT-Institute/BgGPT-7B-Instruct-v0.2 |
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Meet BgGPT-7B, a Bulgarian language model trained from mistralai/Mistral-7B-v0.1. BgGPT is distributed under Apache 2.0 license. |
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This model was created by [`INSAIT Institute`](https://insait.ai/), part of Sofia University, in Sofia, Bulgaria. |
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This is an improved version of the model - v0.2. |
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## Model description |
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The model is continously pretrained to gain its Bulgarian language and culture capabilities using multiple datasets, including Bulgarian web crawl data, a range of specialized Bulgarian datasets sourced by INSAIT Institute, and machine translations of popular English datasets. |
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This Bulgarian data was augmented with English datasets to retain English and logical reasoning skills. |
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The model's tokenizer has been extended to allow for a more efficient encoding of Bulgarian words written in Cyrillic. |
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This not only increases throughput of Cyrillic text but also performance. |
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## Instruction format |
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In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens. |
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The very first instruction should begin with a begin of sequence token `<s>`. Following instructions should not. |
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The assistant generation will be ended by the end-of-sequence token. |
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E.g. |
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``` |
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text = "<s>[INST] Кога е основан Софийският университет? [/INST]" |
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"Софийският университет „Св. Климент Охридски“ е създаден на 1 октомври 1888 г.</s> " |
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"[INST] Кой го е основал? [/INST]" |
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``` |
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This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method: |
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## Benchmarks |
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The model comes with a set of Benchmarks that are translations of the corresponding English-benchmarks. These are provided at [`https://github.com/insait-institute/lm-evaluation-harness-bg`](https://github.com/insait-institute/lm-evaluation-harness-bg) |
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As this is an improved version over version 0.1 of the same model and we include benchmark comparisons. |
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## Summary |
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- **Finetuned from:** [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) |
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- **Model type:** Causal decoder-only transformer language model |
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- **Language:** Bulgarian and English |
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- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html) |
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- **Contact:** [[email protected]](mailto:[email protected]) |
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## Use in 🤗Transformers |
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First install direct dependencies: |
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``` |
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pip install transformers torch accelerate |
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``` |
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If you want faster inference using flash-attention2, you need to install these dependencies: |
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```bash |
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pip install packaging ninja |
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pip install flash-attn |
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``` |
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Then load the model in transformers: |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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model = AutoModelForCausalLM.from_pretrained( |
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model="INSAIT-Institute/BgGPT-7B-Instruct-v0.2", |
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device_map="auto", |
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torch_dtype=torch.bfloat16, |
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use_flash_attn_2=True # optional |
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) |
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``` |
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## Use with GGML / llama.cpp |
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The model in GGUF format [INSAIT-Institute/BgGPT-7B-Instruct-v0.2-GGUF](https://huggingface.co/INSAIT-Institute/BgGPT-7B-Instruct-v0.2-GGUF) |
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