Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) Deacon-1b - GGUF - Model creator: https://huggingface.co/KnutJaegersberg/ - Original model: https://huggingface.co/KnutJaegersberg/Deacon-1b/ | Name | Quant method | Size | | ---- | ---- | ---- | | [Deacon-1b.Q2_K.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q2_K.gguf) | Q2_K | 0.4GB | | [Deacon-1b.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.IQ3_XS.gguf) | IQ3_XS | 0.44GB | | [Deacon-1b.IQ3_S.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.IQ3_S.gguf) | IQ3_S | 0.47GB | | [Deacon-1b.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q3_K_S.gguf) | Q3_K_S | 0.47GB | | [Deacon-1b.IQ3_M.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.IQ3_M.gguf) | IQ3_M | 0.48GB | | [Deacon-1b.Q3_K.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q3_K.gguf) | Q3_K | 0.51GB | | [Deacon-1b.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q3_K_M.gguf) | Q3_K_M | 0.51GB | | [Deacon-1b.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q3_K_L.gguf) | Q3_K_L | 0.55GB | | [Deacon-1b.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.IQ4_XS.gguf) | IQ4_XS | 0.57GB | | [Deacon-1b.Q4_0.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q4_0.gguf) | Q4_0 | 0.59GB | | [Deacon-1b.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.IQ4_NL.gguf) | IQ4_NL | 0.6GB | | [Deacon-1b.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q4_K_S.gguf) | Q4_K_S | 0.6GB | | [Deacon-1b.Q4_K.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q4_K.gguf) | Q4_K | 0.62GB | | [Deacon-1b.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q4_K_M.gguf) | Q4_K_M | 0.62GB | | [Deacon-1b.Q4_1.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q4_1.gguf) | Q4_1 | 0.65GB | | [Deacon-1b.Q5_0.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q5_0.gguf) | Q5_0 | 0.71GB | | [Deacon-1b.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q5_K_S.gguf) | Q5_K_S | 0.71GB | | [Deacon-1b.Q5_K.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q5_K.gguf) | Q5_K | 0.73GB | | [Deacon-1b.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q5_K_M.gguf) | Q5_K_M | 0.73GB | | [Deacon-1b.Q5_1.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q5_1.gguf) | Q5_1 | 0.77GB | | [Deacon-1b.Q6_K.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q6_K.gguf) | Q6_K | 0.84GB | | [Deacon-1b.Q8_0.gguf](https://huggingface.co/RichardErkhov/KnutJaegersberg_-_Deacon-1b-gguf/blob/main/Deacon-1b.Q8_0.gguf) | Q8_0 | 1.09GB | Original model description: --- license: cc-by-nc-4.0 model-index: - name: Deacon-1b results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 32.42 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=KnutJaegersberg/Deacon-1b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 58.62 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=KnutJaegersberg/Deacon-1b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 24.89 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=KnutJaegersberg/Deacon-1b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 35.05 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=KnutJaegersberg/Deacon-1b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 59.59 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=KnutJaegersberg/Deacon-1b name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 0.68 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=KnutJaegersberg/Deacon-1b name: Open LLM Leaderboard --- Base model is appvoid/palmer-001, fine tuned for 3 epochs with Neftune. Prompt Example: ``` ### System: You are an AI assistant. User will give you a task. Your goal is to complete the task as faithfully as you can. While performing the task think step-by-step and justify your steps. ### Instruction: How do you fine tune a large language model? ### Response: ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_KnutJaegersberg__Deacon-1b) | Metric |Value| |---------------------------------|----:| |Avg. |35.21| |AI2 Reasoning Challenge (25-Shot)|32.42| |HellaSwag (10-Shot) |58.62| |MMLU (5-Shot) |24.89| |TruthfulQA (0-shot) |35.05| |Winogrande (5-shot) |59.59| |GSM8k (5-shot) | 0.68|