Neural 4 QA 7b

🚀 Neural-4-QA-7b

Neural-4-QA-7b 是一個融合模型，它使用 LazyMergekit 對以下模型進行了融合，在問答場景中具有出色的表現，為用戶提供更準確、全面的答案。

🚀 快速開始

環境安裝

!pip install -qU transformers accelerate

代碼示例

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/Neural-4-QA-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"])

✨ 主要特性

Neural-4-QA-7b 是通過 LazyMergekit 融合以下模型而成：

• yam-peleg/Experiment21-7B
• CultriX/NeuralTrix-bf16
• louisgrc/Montebello_7B_SLERP
• CorticalStack/pastiche-crown-clown-7b-dare-dpo
• chihoonlee10/T3Q-Mistral-Orca-Math-DPO

📦 安裝指南

使用以下命令安裝所需的庫：

!pip install -qU transformers accelerate

💻 使用示例

基礎用法

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/Neural-4-QA-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"])

📚 詳細文檔

🧩 配置信息

models:
  - model: chihoonlee10/T3Q-Mistral-Orca-Math-DPO
    # No parameters necessary for base model
  - model: yam-peleg/Experiment21-7B
    parameters:
      density: 0.66
      weight: 0.2
  - model: CultriX/NeuralTrix-bf16
    parameters:
      density: 0.55
      weight: 0.2
  - model: louisgrc/Montebello_7B_SLERP
    parameters:
      density: 0.55
      weight: 0.2
  - model: CorticalStack/pastiche-crown-clown-7b-dare-dpo
    parameters:
      density: 0.44
      weight: 0.2
  - model: chihoonlee10/T3Q-Mistral-Orca-Math-DPO
    parameters:
      density: 0.66
      weight: 0.2
merge_method: dare_ties
base_model: chihoonlee10/T3Q-Mistral-Orca-Math-DPO
parameters:
  int8_mask: true
dtype: bfloat16

📄 許可證

本項目採用 apache-2.0 許可證。

📋 模型信息