
# Model Card for Model ID

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## Model Details

### Model Description

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- **Developed by:** C.B. Pronin, A.V. Volosova, A.V. Ostroukh, Yu.N. Strogov, V.V. Kurbatov, A.S. Umarova.
- **Model type:** Base model HuggingFaceH4/zephyr-7b-beta merged with LoRA (Peft) adapter model MexIvanov/zephyr-python-ru trained on a mix of publicly available data and machine-translated synthetic python coding datasets.
- **Language(s) (NLP):** Russian, English, Python
- **License:** MIT
- **Finetuned from model:** HuggingFaceH4/zephyr-7b-beta

### Model Sources

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- **Repository:** Comming soon...
- **Paper:** Comming soon...

## Uses

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An experimental finetune of Zephyr-7b-beta, aimed at improving coding performance and support for coding-related instructions written in Russian language.

### Direct Use

<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->

Instruction-based coding in Python, based of instructions written in natural language (English or Russian)

Prompt template - Zephyr:
```  
<|system|>
</s>
<|user|>
{prompt}</s>
<|assistant|>
```  

## Bias, Risks, and Limitations

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This adapter model is intended (but not limited) for research usage only. It was trained on a code based instruction set and it does not have any moderation mechanisms. Use at your own risk, we are not responsible for any usage or output of this model.

Quote from Zephyr (base-model) repository: "Zephyr-7B-β has not been aligned to human preferences for safety within the RLHF phase or deployed with in-the-loop filtering of responses like ChatGPT, so the model can produce problematic outputs (especially when prompted to do so). It is also unknown what the size and composition of the corpus was used to train the base model (mistralai/Mistral-7B-v0.1), however it is likely to have included a mix of Web data and technical sources like books and code. See the Falcon 180B model card for an example of this."

### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.


## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16

### Framework versions


- PEFT 0.6.2
## Training procedure


The following `bitsandbytes` quantization config was used during training:
- quant_method: QuantizationMethod.BITS_AND_BYTES
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float16

### Framework versions


- PEFT 0.6.2
{"language": ["ru", "en"], "license": "mit", "library_name": "transformers", "tags": ["python", "code"], "datasets": ["MexIvanov/Vezora-Tested-22k-Python-Alpaca-ru", "MexIvanov/CodeExercise-Python-27k-ru", "zelkame/ru-stackoverflow-py"], "base_model": "HuggingFaceH4/zephyr-7b-beta", "pipeline_tag": "conversational", "model-index": [{"name": "zephyr-python-ru-merged", "results": [{"task": {"type": "text-generation"}, "dataset": {"name": "gsm8k", "type": "gsm8k"}, "metrics": [{"type": "Grade School Math 8K (5-Shot)", "value": 32.52, "name": "Grade School Math 8K (5-Shot)"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation"}, "dataset": {"name": "ai2_arc", "type": "ai2_arc"}, "metrics": [{"type": "AI2 Reasoning Challenge (25-Shot)", "value": 56.06, "name": "AI2 Reasoning Challenge (25-Shot)"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation"}, "dataset": {"name": "HellaSwag", "type": "HellaSwag"}, "metrics": [{"type": "HellaSwag (10-Shot)", "value": 82.06, "name": "HellaSwag (10-Shot)"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation"}, "dataset": {"name": "MMLU", "type": "MMLU"}, "metrics": [{"type": "MMLU (5-Shot)", "value": 60.02, "name": "MMLU (5-Shot)"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation"}, "dataset": {"name": "truthfulqa", "type": "truthfulqa"}, "metrics": [{"type": "truthfulqa:mc (0-Shot)", "value": 52.81, "name": "truthfulqa:mc (0-Shot)"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation"}, "dataset": {"name": "winogrande", "type": "winogrande"}, "metrics": [{"type": "winogrande (5-Shot)", "value": 76.95, "name": "winogrande (5-Shot)"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard", "name": "Open LLM Leaderboard"}}]}]}
transformers safetensors mistral text-generation python code conversational ru en dataset:MexIvanov/Vezora-Tested-22k-Python-Alpaca-ru dataset:MexIvanov/CodeExercise-Python-27k-ru dataset:zelkame/ru-stackoverflow-py base_model:HuggingFaceH4/zephyr-7b-beta license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us