初始化项目，由ModelHub XC社区提供模型

Model: CultriX/NeuralTrixlaser-bf16
Source: Original Platform

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- bardsai/jaskier-7b-dpo-v3.3
+- Kquant03/NeuralTrix-7B-dpo-laser
+- CultriX/NeuralTrix-v4-bf16
+- CultriX/NeuralTrix-V2
+base_model:
+- bardsai/jaskier-7b-dpo-v3.3
+- Kquant03/NeuralTrix-7B-dpo-laser
+- CultriX/NeuralTrix-v4-bf16
+- CultriX/NeuralTrix-V2
+license: apache-2.0
+---
+
+# NeuralTrixlaser-bf16
+
+NeuralTrixlaser-bf16 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [bardsai/jaskier-7b-dpo-v3.3](https://huggingface.co/bardsai/jaskier-7b-dpo-v3.3)
+* [Kquant03/NeuralTrix-7B-dpo-laser](https://huggingface.co/Kquant03/NeuralTrix-7B-dpo-laser)
+* [CultriX/NeuralTrix-v4-bf16](https://huggingface.co/CultriX/NeuralTrix-v4-bf16)
+* [CultriX/NeuralTrix-V2](https://huggingface.co/CultriX/NeuralTrix-V2)
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: eren23/dpo-binarized-NeuralTrix-7B
+    # no parameters necessary for base model
+  - model: bardsai/jaskier-7b-dpo-v3.3
+    parameters:
+      density: 0.65
+      weight: 0.4
+  - model: Kquant03/NeuralTrix-7B-dpo-laser
+    parameters:
+      density: 0.6
+      weight: 0.35
+  - model: CultriX/NeuralTrix-v4-bf16
+    parameters:
+      density: 0.55
+      weight: 0.15
+  - model: CultriX/NeuralTrix-V2
+    parameters:
+      density: 0.55
+      weight: 0.15
+merge_method: dare_ties
+base_model: eren23/dpo-binarized-NeuralTrix-7B
+parameters:
+  int8_mask: true
+dtype: bfloat16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "CultriX/"
+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"])
+```