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ExLLaMA V2 quant of speechless-code-mistral-7b-v1.0-6.0bpw-h6-exl2

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README.md ADDED
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+ ---
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+ language:
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+ - en
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ datasets:
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+ - jondurbin/airoboros-2.2
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+ - Open-Orca/OpenOrca
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+ - garage-bAInd/Open-Platypus
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+ - WizardLM/WizardLM_evol_instruct_V2_196k
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+ - TokenBender/python_eval_instruct_51k
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+ tags:
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+ - llama-2
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+ - code
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+ license: llama2
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+ model-index:
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+ - name: SpeechlessCoder
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+ results:
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+ - task:
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+ type: text-generation
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+ dataset:
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+ type: openai_humaneval
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+ name: HumanEval
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+ metrics:
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+ - name: pass@1
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+ type: pass@1
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+ value: 50.0
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+ verified: false
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+ ---
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+
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+ <p><h1> speechless-code-mistral-7b-v1.0 </h1></p>
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+
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+ ### NOTE: Requantized using WizardLM_evol_instruct_V2_196k for calibration
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+
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+ * [AWQ model(s) for GPU inference.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-AWQ)
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+ * [GPTQ models for GPU inference, with multiple quantisation parameter options.](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-GPTQ)
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+ * [2, 3, 4, 5, 6 and 8-bit GGUF models for CPU+GPU inference](https://huggingface.co/TheBloke/speechless-code-mistral-7B-v1.0-GGUF)
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+
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+ Use the following dataset to fine-tune mistralai/Mistral-7B-v0.1 in order to improve the model's reasoning and planning abilities.
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+
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+ Total 201,981 samples.
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+ - jondurbin/airoboros-2.2: Filter categories related to coding, reasoning and planning. 23,462 samples.
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+ - Open-Orca/OpenOrca: Filter the 'cot' category in 1M GPT4 dataset. 74,440 samples.
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+ - garage-bAInd/Open-Platypus: 100%, 24,926 samples.
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+ - WizardLM/WizardLM_evol_instruct_V2_196k: Coding coversation part. 30,185 samples
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+ - TokenBender/python_eval_instruct_51k: “python” in output .40,309 samples
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+ - Spider: 8,659 samples
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+
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+
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+
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+ ## HumanEval
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+
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+ | Metric | Value |
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+ | --- | --- |
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+ | humaneval-python | 50.0|
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+
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+ [Big Code Models Leaderboard](https://huggingface.co/spaces/bigcode/bigcode-models-leaderboard)
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+
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+ CodeLlama-34B-Python: 53.29
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+
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+ CodeLlama-34B-Instruct: 50.79
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+
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+ CodeLlama-13B-Instruct: 50.6
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+
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+ CodeLlama-34B: 45.11
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+
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+ CodeLlama-13B-Python: 42.89
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+
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+ CodeLlama-13B: 35.07
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+
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+ ## lm-evaluation-harness
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+
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+ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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+ | Metric | Value |
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+ | --- | --- |
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+ | ARC |59.64 |
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+ | HellaSwag |82.25 |
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+ | MMLU | 61.33 |
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+ | TruthfulQA | 48.45 |
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+ | Average | 62.92 |
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+
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+ ## Parameters
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+
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+ | | |
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+ |------ | ------ |
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+ | lr | 2e-4 |
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+ | lr_scheduler_type | cosine |
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+ | weight_decay | 0.0 |
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+ | optim | paged_adamw_8bit |
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+ | flash_attention | True |
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+ | rerope | False |
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+ | max_new_tokens | 4096 |
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+ | num_train_epochs | 2 |
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+ | bits | 4 |
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+ | lora_r | 64 |
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+ | lora_alpha | 16 |
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+ | lora_dropout | 0.05 |
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+ | double_quant | True |
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+ | quant_type | nf4 |
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+ | dataset_format | airoboros |
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+ | mini_batch_size | 2 |
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+ | grandient_accumulation_steps | 32 |
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+ | bf16 | True |
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+
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+ A40-48G x 2
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+
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+ | | |
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+ |------ | ------ |
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+ | epoch | 2.0 |
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+ | etrain_loss | 0.5 |
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+ | etrain_runtime | 1 day, 10:25:26.77 |
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+ | etrain_samples_per_second | 3.194 |
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+ | etrain_steps_per_second | 0.025 |
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+ | eeval_loss | 0.5146 |
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+ | eeval_runtime | 0:00:25.04 |
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+ | eeval_samples_per_second | 7.985 |
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+ | eeval_steps_per_second | |
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+ "architectures": [
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+ "torch_dtype": "float16",
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+ "vocab_size": 32000
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