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--- |
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license: apache-2.0 |
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tags: |
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- code |
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- mistral |
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--- |
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# Mistral-7B-codealpaca |
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I am thrilled to introduce my Mistral-7B-codealpaca model. This variant is optimized and demonstrates potential in assisting developers as a coding companion. I welcome contributions from testers and enthusiasts to help evaluate its performance. |
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## Training Details |
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I trained the model using 3xRTX 3090 for 118 hours. |
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[](https://github.com/OpenAccess-AI-Collective/axolotl) |
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## Quantised Model Links: |
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1. https://huggingface.co/TheBloke/Mistral-7B-codealpaca-lora-GPTQ |
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2. https://huggingface.co/TheBloke/Mistral-7B-codealpaca-lora-GGUF |
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3. https://huggingface.co/TheBloke/Mistral-7B-codealpaca-lora-AWQ |
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## Download by qBittorrent: |
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#### Torrent file: https://github.com/Nondzu/LlamaTor/blob/torrents/torrents/Nondzu_Mistral-7B-codealpaca-lora.torrent |
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## Dataset: |
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- Dataset Name: theblackcat102/evol-codealpaca-v1 |
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- Dataset Link: [theblackcat102/evol-codealpaca-v1](https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1) |
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## Prompt template: Alpaca |
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``` |
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Below is an instruction that describes a task. Write a response that appropriately completes the request. |
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### Instruction: |
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{prompt} |
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### Response: |
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``` |
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## Performance (evalplus) |
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Human eval plus: https://github.com/evalplus/evalplus |
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Well, the results are better than I expected: |
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- Base: `{'pass@1': 0.47560975609756095}` |
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- Base + Extra: `{'pass@1': 0.4329268292682927}` |
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For reference, I've provided the performance of the original Mistral model alongside my Mistral-7B-code-16k-qlora model. |
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** [Nondzu/Mistral-7B-code-16k-qlora](https://huggingface.co/Nondzu/Mistral-7B-code-16k-qlora)**: |
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- Base: `{'pass@1': 0.3353658536585366}` |
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- Base + Extra: `{'pass@1': 0.2804878048780488}` |
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** [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)**: |
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- Base: `{'pass@1': 0.2926829268292683}` |
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- Base + Extra: `{'pass@1': 0.24390243902439024}` |
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## Model Configuration: |
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Here are the configurations for my Mistral-7B-codealpaca-lora: |
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```yaml |
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base_model: mistralai/Mistral-7B-Instruct-v0.1 |
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base_model_config: mistralai/Mistral-7B-Instruct-v0.1 |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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load_in_8bit: true |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: theblackcat102/evol-codealpaca-v1 |
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type: oasst |
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dataset_prepared_path: |
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val_set_size: 0.01 |
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output_dir: ./nondzu/Mistral-7B-codealpaca-test14 |
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adapter: lora |
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sequence_len: 4096 |
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sample_packing: true |
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pad_to_sequence_len: true |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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lora_target_linear: true |
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``` |
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## Additional Projects: |
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For other related projects, you can check out: |
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- [LlamaTor on GitHub](https://github.com/Nondzu/LlamaTor) |
