初始化项目，由ModelHub XC社区提供模型

Model: Kquant03/NeuralTrix-7B-dpo-laser
Source: Original Platform

.gitattributes

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+pytorch_model-00002-of-00002.bin filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- mlabonne/OmniBeagle-7B
+- flemmingmiguel/MBX-7B-v3
+- AiMavenAi/AiMaven-Prometheus
+base_model:
+- mlabonne/OmniBeagle-7B
+- flemmingmiguel/MBX-7B-v3
+- AiMavenAi/AiMaven-Prometheus
+license: apache-2.0
+---
+
+
+# NeuralTrix-7B-v1
+
+NeuralTrix-7B-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [mlabonne/OmniBeagle-7B](https://huggingface.co/mlabonne/OmniBeagle-7B)
+* [flemmingmiguel/MBX-7B-v3](https://huggingface.co/flemmingmiguel/MBX-7B-v3)
+* [AiMavenAi/AiMaven-Prometheus](https://huggingface.co/AiMavenAi/AiMaven-Prometheus)
+
+It was then trained with DPO using: 
+* https://huggingface.co/datasets/jondurbin/truthy-dpo-v0.1
+
+## 🧩 Configuration
+
+```yaml
+models:
+  - model: mistralai/Mistral-7B-v0.1
+    # no parameters necessary for base model
+  - model: mlabonne/OmniBeagle-7B
+    parameters:
+      density: 0.65
+      weight: 0.4
+  - model: flemmingmiguel/MBX-7B-v3
+    parameters:
+      density: 0.6
+      weight: 0.35
+  - model: AiMavenAi/AiMaven-Prometheus
+    parameters:
+      density: 0.6
+      weight: 0.35
+merge_method: dare_ties
+base_model: mistralai/Mistral-7B-v0.1
+parameters:
+  int8_mask: true
+dtype: float16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "CultriX/NeuralTrix-7B-v1"
+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"])
+```

added_tokens.json

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+{
+  "</s>": 2,
+  "<s>": 1,
+  "<unk>": 0
+}

config.json

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+{
+  "_name_or_path": "CultriX/NeuralTrix-7B-dpo",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.34.0",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.34.0"
+}

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special_tokens_map.json

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tokenizer_config.json

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