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Quantization made by Richard Erkhov.
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RolePlayLake-7B - GGUF
- Model creator: https://huggingface.co/fhai50032/
- Original model: https://huggingface.co/fhai50032/RolePlayLake-7B/
| Name | Quant method | Size |
| ---- | ---- | ---- |
| [RolePlayLake-7B.Q2_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q2_K.gguf) | Q2_K | 2.53GB |
| [RolePlayLake-7B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.IQ3_XS.gguf) | IQ3_XS | 2.81GB |
| [RolePlayLake-7B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.IQ3_S.gguf) | IQ3_S | 2.96GB |
| [RolePlayLake-7B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q3_K_S.gguf) | Q3_K_S | 2.95GB |
| [RolePlayLake-7B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.IQ3_M.gguf) | IQ3_M | 3.06GB |
| [RolePlayLake-7B.Q3_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q3_K.gguf) | Q3_K | 3.28GB |
| [RolePlayLake-7B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q3_K_M.gguf) | Q3_K_M | 3.28GB |
| [RolePlayLake-7B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q3_K_L.gguf) | Q3_K_L | 3.56GB |
| [RolePlayLake-7B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.IQ4_XS.gguf) | IQ4_XS | 3.67GB |
| [RolePlayLake-7B.Q4_0.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q4_0.gguf) | Q4_0 | 3.83GB |
| [RolePlayLake-7B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.IQ4_NL.gguf) | IQ4_NL | 3.87GB |
| [RolePlayLake-7B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q4_K_S.gguf) | Q4_K_S | 3.86GB |
| [RolePlayLake-7B.Q4_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q4_K.gguf) | Q4_K | 4.07GB |
| [RolePlayLake-7B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q4_K_M.gguf) | Q4_K_M | 4.07GB |
| [RolePlayLake-7B.Q4_1.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q4_1.gguf) | Q4_1 | 4.24GB |
| [RolePlayLake-7B.Q5_0.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q5_0.gguf) | Q5_0 | 4.65GB |
| [RolePlayLake-7B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q5_K_S.gguf) | Q5_K_S | 4.65GB |
| [RolePlayLake-7B.Q5_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q5_K.gguf) | Q5_K | 4.78GB |
| [RolePlayLake-7B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q5_K_M.gguf) | Q5_K_M | 4.78GB |
| [RolePlayLake-7B.Q5_1.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q5_1.gguf) | Q5_1 | 5.07GB |
| [RolePlayLake-7B.Q6_K.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q6_K.gguf) | Q6_K | 5.53GB |
| [RolePlayLake-7B.Q8_0.gguf](https://huggingface.co/RichardErkhov/fhai50032_-_RolePlayLake-7B-gguf/blob/main/RolePlayLake-7B.Q8_0.gguf) | Q8_0 | 7.17GB |
Original model description:
---
license: apache-2.0
tags:
- merge
- mergekit
- mistral
- SanjiWatsuki/Silicon-Maid-7B
- senseable/WestLake-7B-v2
base_model:
- SanjiWatsuki/Silicon-Maid-7B
- senseable/WestLake-7B-v2
model-index:
- name: RolePlayLake-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: 70.56
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/RolePlayLake-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: 87.42
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/RolePlayLake-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: 64.55
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/RolePlayLake-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: 64.38
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/RolePlayLake-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: 83.27
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/RolePlayLake-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: 65.05
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fhai50032/RolePlayLake-7B
name: Open LLM Leaderboard
---
# RolePlayLake-7B
RolePlayLake-7B is a merge of the following models :
* [SanjiWatsuki/Silicon-Maid-7B](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B)
* [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2)
`In my current testing RolePlayLake is Better than Silicon_Maid in RP and More Uncensored Than WestLake`
`I would try to only merge Uncensored Models with Baising towards Chat rather than Instruct `
## 🧩 Configuration
```yaml
slices:
- sources:
- model: SanjiWatsuki/Silicon-Maid-7B
layer_range: [0, 32]
- model: senseable/WestLake-7B-v2
layer_range: [0, 32]
merge_method: slerp
base_model: senseable/WestLake-7B-v2
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 = "fhai50032/RolePlayLake-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"])
```
# Why I Merged WestLake and Silicon Maid
Merged WestLake and Silicon Maid for a unique blend:
1. **EQ-Bench Dominance:** WestLake's 79.75 EQ-Bench score. (Maybe Contaminated)
2. **Charm and Role-Play:** Silicon's explicit charm and WestLake's role-play prowess.
3. **Config Synergy:** Supports lots of prompt format out of the gate and has a very nice synergy
Result: RolePlayLake-7B, a linguistic fusion with EQ-Bench supremacy and captivating role-play potential.
# [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__RolePlayLake-7B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |72.54|
|AI2 Reasoning Challenge (25-Shot)|70.56|
|HellaSwag (10-Shot) |87.42|
|MMLU (5-Shot) |64.55|
|TruthfulQA (0-shot) |64.38|
|Winogrande (5-shot) |83.27|
|GSM8k (5-shot) |65.05|