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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+A-I-0xtom-7B-slerp - GGUF
+- Model creator: https://huggingface.co/InnerI/
+- Original model: https://huggingface.co/InnerI/A-I-0xtom-7B-slerp/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [A-I-0xtom-7B-slerp.Q2_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q2_K.gguf) | Q2_K | 2.53GB |
+| [A-I-0xtom-7B-slerp.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.IQ3_XS.gguf) | IQ3_XS | 2.81GB |
+| [A-I-0xtom-7B-slerp.IQ3_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.IQ3_S.gguf) | IQ3_S | 2.96GB |
+| [A-I-0xtom-7B-slerp.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q3_K_S.gguf) | Q3_K_S | 2.95GB |
+| [A-I-0xtom-7B-slerp.IQ3_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.IQ3_M.gguf) | IQ3_M | 3.06GB |
+| [A-I-0xtom-7B-slerp.Q3_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q3_K.gguf) | Q3_K | 3.28GB |
+| [A-I-0xtom-7B-slerp.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q3_K_M.gguf) | Q3_K_M | 3.28GB |
+| [A-I-0xtom-7B-slerp.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q3_K_L.gguf) | Q3_K_L | 3.56GB |
+| [A-I-0xtom-7B-slerp.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.IQ4_XS.gguf) | IQ4_XS | 3.67GB |
+| [A-I-0xtom-7B-slerp.Q4_0.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q4_0.gguf) | Q4_0 | 3.83GB |
+| [A-I-0xtom-7B-slerp.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.IQ4_NL.gguf) | IQ4_NL | 3.87GB |
+| [A-I-0xtom-7B-slerp.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q4_K_S.gguf) | Q4_K_S | 3.86GB |
+| [A-I-0xtom-7B-slerp.Q4_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q4_K.gguf) | Q4_K | 4.07GB |
+| [A-I-0xtom-7B-slerp.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q4_K_M.gguf) | Q4_K_M | 4.07GB |
+| [A-I-0xtom-7B-slerp.Q4_1.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q4_1.gguf) | Q4_1 | 4.24GB |
+| [A-I-0xtom-7B-slerp.Q5_0.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q5_0.gguf) | Q5_0 | 4.65GB |
+| [A-I-0xtom-7B-slerp.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q5_K_S.gguf) | Q5_K_S | 4.65GB |
+| [A-I-0xtom-7B-slerp.Q5_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q5_K.gguf) | Q5_K | 4.78GB |
+| [A-I-0xtom-7B-slerp.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q5_K_M.gguf) | Q5_K_M | 4.78GB |
+| [A-I-0xtom-7B-slerp.Q5_1.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q5_1.gguf) | Q5_1 | 5.07GB |
+| [A-I-0xtom-7B-slerp.Q6_K.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q6_K.gguf) | Q6_K | 5.53GB |
+| [A-I-0xtom-7B-slerp.Q8_0.gguf](https://huggingface.co/RichardErkhov/InnerI_-_A-I-0xtom-7B-slerp-gguf/blob/main/A-I-0xtom-7B-slerp.Q8_0.gguf) | Q8_0 | 7.17GB |
+
+
+
+
+Original model description:
+---
+license: apache-2.0
+tags:
+- merge
+- mergekit
+- lazymergekit
+- 0x0dad0/nous_nous_v2_0
+- tomaszki/nous-thirty
+base_model:
+- 0x0dad0/nous_nous_v2_0
+- tomaszki/nous-thirty
+model-index:
+- name: A-I-0xtom-7B-slerp
+  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: 58.19
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InnerI/A-I-0xtom-7B-slerp
+      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: 77.64
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InnerI/A-I-0xtom-7B-slerp
+      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: 58.74
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InnerI/A-I-0xtom-7B-slerp
+      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: 54.78
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InnerI/A-I-0xtom-7B-slerp
+      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: 73.24
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InnerI/A-I-0xtom-7B-slerp
+      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: 40.18
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=InnerI/A-I-0xtom-7B-slerp
+      name: Open LLM Leaderboard
+---
+
+# A-I-0xtom-7B-slerp
+
+A-I-0xtom-7B-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [0x0dad0/nous_nous_v2_0](https://huggingface.co/0x0dad0/nous_nous_v2_0)
+* [tomaszki/nous-thirty](https://huggingface.co/tomaszki/nous-thirty)
+
+# Avg model loss 0.3912096044793725
+I used this testing script that loads your local model, pulls the latest data from cortex and calculates the loss: 
+[avg loss script](https://gist.github.com/romanorac/59ccde7cbf07d8950ef9fb5b5db6a24e)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: 0x0dad0/nous_nous_v2_0
+        layer_range: [0, 32]
+      - model: tomaszki/nous-thirty
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: 0x0dad0/nous_nous_v2_0
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "InnerI/A-I-0xtom-7B-slerp"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```
+# [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_InnerI__A-I-0xtom-7B-slerp)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |60.46|
+|AI2 Reasoning Challenge (25-Shot)|58.19|
+|HellaSwag (10-Shot)              |77.64|
+|MMLU (5-Shot)                    |58.74|
+|TruthfulQA (0-shot)              |54.78|
+|Winogrande (5-shot)              |73.24|
+|GSM8k (5-shot)                   |40.18|
+
+
+