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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)
+
+
+BeagleLake-7B - GGUF
+- Model creator: https://huggingface.co/fhai50032/
+- Original model: https://huggingface.co/fhai50032/BeagleLake-7B/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [BeagleLake-7B.Q2_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q2_K.gguf) | Q2_K | 2.53GB |
+| [BeagleLake-7B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.IQ3_XS.gguf) | IQ3_XS | 2.81GB |
+| [BeagleLake-7B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.IQ3_S.gguf) | IQ3_S | 2.96GB |
+| [BeagleLake-7B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q3_K_S.gguf) | Q3_K_S | 2.95GB |
+| [BeagleLake-7B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.IQ3_M.gguf) | IQ3_M | 3.06GB |
+| [BeagleLake-7B.Q3_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q3_K.gguf) | Q3_K | 3.28GB |
+| [BeagleLake-7B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q3_K_M.gguf) | Q3_K_M | 3.28GB |
+| [BeagleLake-7B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q3_K_L.gguf) | Q3_K_L | 3.56GB |
+| [BeagleLake-7B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.IQ4_XS.gguf) | IQ4_XS | 3.67GB |
+| [BeagleLake-7B.Q4_0.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q4_0.gguf) | Q4_0 | 3.83GB |
+| [BeagleLake-7B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.IQ4_NL.gguf) | IQ4_NL | 3.87GB |
+| [BeagleLake-7B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q4_K_S.gguf) | Q4_K_S | 3.86GB |
+| [BeagleLake-7B.Q4_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q4_K.gguf) | Q4_K | 4.07GB |
+| [BeagleLake-7B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q4_K_M.gguf) | Q4_K_M | 4.07GB |
+| [BeagleLake-7B.Q4_1.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q4_1.gguf) | Q4_1 | 4.24GB |
+| [BeagleLake-7B.Q5_0.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q5_0.gguf) | Q5_0 | 4.65GB |
+| [BeagleLake-7B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q5_K_S.gguf) | Q5_K_S | 4.65GB |
+| [BeagleLake-7B.Q5_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q5_K.gguf) | Q5_K | 4.78GB |
+| [BeagleLake-7B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q5_K_M.gguf) | Q5_K_M | 4.78GB |
+| [BeagleLake-7B.Q5_1.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q5_1.gguf) | Q5_1 | 5.07GB |
+| [BeagleLake-7B.Q6_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q6_K.gguf) | Q6_K | 5.53GB |
+| [BeagleLake-7B.Q8_0.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_BeagleLake-7B-gguf/blob/main/BeagleLake-7B.Q8_0.gguf) | Q8_0 | 7.17GB |
+
+
+
+
+Original model description:
+---
+license: apache-2.0
+tags:
+- merge
+- mergekit
+- mistral
+- fhai50032/RolePlayLake-7B
+- mlabonne/NeuralBeagle14-7B
+base_model:
+- fhai50032/RolePlayLake-7B
+- mlabonne/NeuralBeagle14-7B
+model-index:
+- name: BeagleLake-7B
+  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: 70.39
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/BeagleLake-7B
+      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: 87.38
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/BeagleLake-7B
+      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: 64.25
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/BeagleLake-7B
+      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: 64.92
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/BeagleLake-7B
+      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: 83.19
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/BeagleLake-7B
+      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: 63.91
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/BeagleLake-7B
+      name: Open LLM Leaderboard
+---
+
+# BeagleLake-7B
+
+BeagleLake-7B is a merge of the following models :
+* [fhai50032/RolePlayLake-7B](https://huggingface.co/fhai50032/RolePlayLake-7B)
+* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
+
+
+Merging models are not powerful but are helpful in the case that it can work like Transfer Learning similar idk.. But they perform high on Leaderboard 
+For ex.  NeuralBeagle is powerful model with lot of potential to grow and RolePlayLake is Suitable for RP (No-Simping) and is significantly uncensored and nice obligations
+Fine-tuning a Merged model as a base model is surely a way to look forward and see a lot of potential going forward..
+
+Much thanks to [Charles Goddard](https://huggingface.co/chargoddard) for making simple interface ['mergekit' ](https://github.com/cg123/mergekit)
+
+
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: mlabonne/NeuralBeagle14-7B
+# no params for base model
+  - model: fhai50032/RolePlayLake-7B
+    parameters:
+      weight: 0.8
+      density: 0.6
+  - model: mlabonne/NeuralBeagle14-7B
+    parameters:
+      weight: 0.3
+      density: [0.1,0.3,0.5,0.7,1]
+merge_method: dare_ties
+base_model: mlabonne/NeuralBeagle14-7B
+parameters:
+  normalize: true
+  int8_mask: true
+dtype: float16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "fhai50032/BeagleLake-7B"
+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_fhai50032__BeagleLake-7B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |72.34|
+|AI2 Reasoning Challenge (25-Shot)|70.39|
+|HellaSwag (10-Shot)              |87.38|
+|MMLU (5-Shot)                    |64.25|
+|TruthfulQA (0-shot)              |64.92|
+|Winogrande (5-shot)              |83.19|
+|GSM8k (5-shot)                   |63.91|
+
+
+