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NinjaDolphin-7B - GGUF
- Model creator: https://huggingface.co/FelixChao/
- Original model: https://huggingface.co/FelixChao/NinjaDolphin-7B/
Name | Quant method | Size |
---|---|---|
NinjaDolphin-7B.Q2_K.gguf | Q2_K | 2.53GB |
NinjaDolphin-7B.IQ3_XS.gguf | IQ3_XS | 2.81GB |
NinjaDolphin-7B.IQ3_S.gguf | IQ3_S | 2.96GB |
NinjaDolphin-7B.Q3_K_S.gguf | Q3_K_S | 2.95GB |
NinjaDolphin-7B.IQ3_M.gguf | IQ3_M | 3.06GB |
NinjaDolphin-7B.Q3_K.gguf | Q3_K | 3.28GB |
NinjaDolphin-7B.Q3_K_M.gguf | Q3_K_M | 3.28GB |
NinjaDolphin-7B.Q3_K_L.gguf | Q3_K_L | 3.56GB |
NinjaDolphin-7B.IQ4_XS.gguf | IQ4_XS | 3.67GB |
NinjaDolphin-7B.Q4_0.gguf | Q4_0 | 3.83GB |
NinjaDolphin-7B.IQ4_NL.gguf | IQ4_NL | 3.87GB |
NinjaDolphin-7B.Q4_K_S.gguf | Q4_K_S | 3.86GB |
NinjaDolphin-7B.Q4_K.gguf | Q4_K | 4.07GB |
NinjaDolphin-7B.Q4_K_M.gguf | Q4_K_M | 4.07GB |
NinjaDolphin-7B.Q4_1.gguf | Q4_1 | 4.24GB |
NinjaDolphin-7B.Q5_0.gguf | Q5_0 | 4.65GB |
NinjaDolphin-7B.Q5_K_S.gguf | Q5_K_S | 4.65GB |
NinjaDolphin-7B.Q5_K.gguf | Q5_K | 4.78GB |
NinjaDolphin-7B.Q5_K_M.gguf | Q5_K_M | 4.78GB |
NinjaDolphin-7B.Q5_1.gguf | Q5_1 | 5.07GB |
NinjaDolphin-7B.Q6_K.gguf | Q6_K | 5.53GB |
NinjaDolphin-7B.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
license: apache-2.0 tags: - merge - beowolx/CodeNinja-1.0-OpenChat-7B - beowolx/MistralHermes-CodePro-7B-v1 model-index: - name: NinjaDolphin-7B results: - task: type: text-generation # Required. Example: automatic-speech-recognition dataset: type: openai_humaneval # Required. Example: common_voice. Use dataset id from https://hf.co/datasets name: HumanEval # Required. A pretty name for the dataset. Example: Common Voice (French) metrics: - type: pass@1 # Required. Example: wer. Use metric id from https://hf.co/metrics value: 52.4390243902439 # Required. Example: 20.90 name: pass@1 # Optional. Example: Test WER verified: false
NinjaDolphin-7B
NinjaDolphin-7B is a merge of the following models using:
Improving coding ability from FelixChao/WizardDolphin-7B.
HumanEval (uninstructed and no post-process)
Metric | Value |
---|---|
humaneval-python | 52.4390243902439 |
𧩠Configuration
models:
- model: FelixChao/WizardDolphin-7B
- model: beowolx/CodeNinja-1.0-OpenChat-7B
parameters:
density: 0.53
weight: 0.3
- model: beowolx/MistralHermes-CodePro-7B-v1
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: FelixChao/WizardDolphin-7B
parameters:
int8_mask: true
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "FelixChao/NinjaDolphin-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
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 69.74 |
AI2 Reasoning Challenge (25-Shot) | 65.61 |
HellaSwag (10-Shot) | 85.35 |
MMLU (5-Shot) | 64.43 |
TruthfulQA (0-shot) | 54.94 |
Winogrande (5-shot) | 80.27 |
GSM8k (5-shot) | 67.85 |
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