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Model: INSAIT-Institute/BgGPT-7B-Instruct-v0.2
Source: Original Platform

README.md

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+---
+base_model: mistralai/Mistral-7B-v0.1
+tags:
+  - mistral
+  - instruct
+  - bggpt
+  - insait
+language:
+- bg
+- en
+library_name: transformers
+pipeline_tag: text-generation
+license: apache-2.0
+---
+# INSAIT-Institute/BgGPT-7B-Instruct-v0.2
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/637e1f8cf7e01589cc17bf7e/p6d0YFHjWCQ3S12jWqO1m.png)
+
+Meet BgGPT-7B, a Bulgarian language model trained from mistralai/Mistral-7B-v0.1. BgGPT is distributed under Apache 2.0 license.
+
+This model was created by [`INSAIT Institute`](https://insait.ai/), part of Sofia University, in Sofia, Bulgaria.
+
+This is an improved version of the model - v0.2.
+
+## Model description
+
+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. 
+This Bulgarian data was augmented with English datasets to retain English and logical reasoning skills.
+
+The model's tokenizer has been extended to allow for a more efficient encoding of Bulgarian words written in Cyrillic. 
+This not only increases throughput of Cyrillic text but also performance. 
+
+## Instruction format
+
+In order to leverage instruction fine-tuning, your prompt should be surrounded by `[INST]` and `[/INST]` tokens. 
+The very first instruction should begin with a begin of sequence token `<s>`. Following instructions should not. 
+The assistant generation will be ended by the end-of-sequence token.
+
+E.g.
+```
+text = "<s>[INST] Кога е основан Софийският университет? [/INST]"
+"Софийският университет „Св. Климент Охридски“ е създаден на 1 октомври 1888 г.</s> "
+"[INST] Кой го е основал? [/INST]"
+```
+
+This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method:
+
+## Benchmarks
+
+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)
+
+As this is an improved version over version 0.1 of the same model and we include benchmark comparisons.
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/637e1f8cf7e01589cc17bf7e/aZAEv5qyLcPn5p4KrHpEw.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/637e1f8cf7e01589cc17bf7e/6PafMC6StfUaPY1N8Xrta.png)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/637e1f8cf7e01589cc17bf7e/L1bKXq4Xiik1ZbTDuCnxj.png)
+
+## Summary
+- **Finetuned from:** [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+- **Model type:** Causal decoder-only transformer language model
+- **Language:** Bulgarian and English
+- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0.html)
+- **Contact:** [bggpt@insait.ai](mailto:bggpt@insait.ai)
+
+## Use in 🤗Transformers
+First install direct dependencies:
+```
+pip install transformers torch accelerate
+```
+If you want faster inference using flash-attention2, you need to install these dependencies:
+```bash
+pip install packaging ninja
+pip install flash-attn
+```
+Then load the model in transformers:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+model = AutoModelForCausalLM.from_pretrained(
+    model="INSAIT-Institute/BgGPT-7B-Instruct-v0.2",
+    device_map="auto",
+    torch_dtype=torch.bfloat16,
+    use_flash_attn_2=True # optional
+)
+```
+
+## Use with GGML / llama.cpp
+
+The model in GGUF format [INSAIT-Institute/BgGPT-7B-Instruct-v0.2-GGUF](https://huggingface.co/INSAIT-Institute/BgGPT-7B-Instruct-v0.2-GGUF)