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README.md

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+---
+base_model:
+- tokyotech-llm/Swallow-70b-NVE-instruct-hf
+- dreamgen/opus-v0.5-70b
+- GOAT-AI/GOAT-70B-Storytelling
+- Doctor-Shotgun/lzlv-limarpv3-l2-70b
+- alac/Waxwing-Storytelling-70B-LoRA
+tags:
+- mergekit
+- merge
+language:
+  - en
+  - ja
+library_name: transformers
+pipeline_tag: text-generation
+license: llama2
+model_type: llama
+---
+# Swallow-70b-NVE-RP
+
+**Important Notice:**
+
+For personal and academic use only.
+
+## Description
+
+This model is suitable for role-playing and storytelling, but it's not a great model for multi-turn chat.
+
+This was created for personal and academic use only. This merge model uses only fine-tune models of Llama2, but some of the models used include those whose licenses for commercial use are unclear.
+
+If there is a license problem, the rights holder should contact me directly. No license changes will be made due to contact from others.
+
+## Test environment
+
+This model was tested using [text-generation-webui](https://github.com/oobabooga/text-generation-webui/tree/main). I use preset `simple-1` and `Null preset` for Generation.
+
+### Recommendation
+
+Use `simple-1` settings:
+- temperature: 0.7
+- top_p: 0.9
+- repetition_penalty: 1.15
+- top_k: 20
+
+### Tested `temperature` Range
+
+- temperature: 0.3 - 1.0
+
+### Tested `repetition_penalty` Range
+
+- repetition_penalty: 1.0 - 1.15
+
+## Prompt template
+
+### Swallow Style (Alpaca format)
+
+```
+以下に、あるタスクを説明する指示があり、それに付随する入力が更なる文脈を提供しています。リクエストを適切に完了するための回答を記述してください。
+
+### 指示:
+{instruction}
+
+### 応答:
+
+```
+
+Although not fully tested, [Doctor-Shotgun/lzlv-limarpv3-l2-70b](Doctor-Shotgun/lzlv-limarpv3-l2-70b) and [alac/Waxwing-Storytelling-70B-LoRA](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA) prompt styles are also available.
+
+## Use the instruct model
+
+```
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "nitky/Swallow-70b-NVE-RP"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, low_cpu_mem_usage=True, device_map="auto", load_in_4bit = True)
+
+
+PROMPT_DICT = {
+    "prompt_input": (
+        "以下に、あるタスクを説明する指示があり、それに付随する入力が更なる文脈を提供しています。"
+        "リクエストを適切に完了するための回答を記述してください。\n\n"
+        "### 指示:\n{instruction}\n\n### 入力:\n{input}\n\n### 応答:"
+
+    ),
+    "prompt_no_input": (
+        "以下に、あるタスクを説明する指示があります。"
+        "リクエストを適切に完了するための回答を記述してください。\n\n"
+        "### 指示:\n{instruction}\n\n### 応答:"
+    ),
+}
+
+def create_prompt(instruction, input=None):
+    """
+    Generates a prompt based on the given instruction and an optional input.
+    If input is provided, it uses the 'prompt_input' template from PROMPT_DICT.
+    If no input is provided, it uses the 'prompt_no_input' template.
+
+    Args:
+        instruction (str): The instruction describing the task.
+        input (str, optional): Additional input providing context for the task. Default is None.
+
+    Returns:
+        str: The generated prompt.
+    """
+    if input:
+        # Use the 'prompt_input' template when additional input is provided
+        return PROMPT_DICT["prompt_input"].format(instruction=instruction, input=input)
+    else:
+        # Use the 'prompt_no_input' template when no additional input is provided
+        return PROMPT_DICT["prompt_no_input"].format(instruction=instruction)
+
+# Example usage
+instruction_example = "以下のトピックに関する詳細な情報を提供してください。"
+input_example = "東京工業大学の主なキャンパスについて教えてください"
+prompt = create_prompt(instruction_example, input_example)
+
+input_ids = tokenizer.encode(
+    prompt,
+    add_special_tokens=False,
+    return_tensors="pt"
+)
+
+tokens = model.generate(
+    input_ids.to(device=model.device),
+    max_new_tokens=200,
+    temperature=0.7,
+    top_p=0.9,
+    repetition_penalty=1.15,
+    top_k=20,
+    do_sample=True,
+)
+
+out = tokenizer.decode(tokens[0], skip_special_tokens=True)
+print(out)
+
+```
+
+## Merge Details
+### Merge Method
+
+This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) and the SLERP merge method using [tokyotech-llm/Swallow-70b-NVE-instruct-hf](https://huggingface.co/tokyotech-llm/Swallow-70b-NVE-instruct-hf) as a base.
+
+### Models Merged
+
+The following models were included in the merge:
+* [GOAT-AI/GOAT-70B-Storytelling](https://huggingface.co/GOAT-AI/GOAT-70B-Storytelling)
+* [dreamgen/opus-v0.5-70b](https://huggingface.co/dreamgen/opus-v0.5-70b)
+* [Doctor-Shotgun/lzlv-limarpv3-l2-70b](Doctor-Shotgun/lzlv-limarpv3-l2-70b)
+* [LoRA] [alac/Waxwing-Storytelling-70B-LoRA](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA)
+
+### Configuration
+
+Command example:
+
+```bash
+# please change the path and options according to your environment
+mergekit-mega --cuda --lora-merge-cache ~/text-generation-webui/loras/models--alac--Waxwing-Storytelling-70B-LoRA Swallow-70b-NVE-RP.yml ~/text-generation-webui/models
+```
+
+The following YAML configuration was used to produce this model:
+
+```yaml
+models:
+  - model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+    # no parameters necessary for base model
+  - model: GOAT-AI/GOAT-70B-Storytelling # storytelling
+    parameters:
+      density: 1
+      weight: 0.25
+  - model: dreamgen/opus-v0.5-70b # creative roleplay
+    parameters:
+      density: 1
+      weight: 0.25
+merge_method: dare_ties
+base_model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+dtype: bfloat16
+name: Swallow-70b-NVE-RP-base
+---
+models:
+  - model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+    # no parameters necessary for base model
+  - model: Doctor-Shotgun/lzlv-limarpv3-l2-70b # roleplay configuration
+    parameters:
+      density: 1
+      weight: 0.25
+merge_method: dare_ties
+base_model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+dtype: bfloat16
+name: Swallow-70b-NVE-RP-flavor
+---
+slices:
+  - sources:
+      - model: Swallow-70b-NVE-RP-base
+        layer_range: [0, 80]
+      - model: Swallow-70b-NVE-RP-flavor
+        layer_range: [0, 80]
+merge_method: slerp
+base_model: Swallow-70b-NVE-RP-base
+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 # fallback for rest of tensors
+dtype: bfloat16
+name: Swallow-70b-NVE-RP
+
+```

config.json

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+{
+  "_name_or_path": "nitky/Swallow-70b-NVE-RP",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 8192,
+  "initializer_range": 0.02,
+  "intermediate_size": 28672,
+  "max_position_embeddings": 4096,
+  "max_sequence_length": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 80,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+models:
+  - model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+    # no parameters necessary for base model
+  - model: GOAT-AI/GOAT-70B-Storytelling # storytelling
+    parameters:
+      density: 1
+      weight: 0.25
+  - model: dreamgen/opus-v0.5-70b # creative roleplay
+    parameters:
+      density: 1
+      weight: 0.25
+merge_method: dare_ties
+base_model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+dtype: bfloat16
+name: Swallow-70b-NVE-RP-base
+---
+models:
+  - model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+    # no parameters necessary for base model
+  - model: Doctor-Shotgun/lzlv-limarpv3-l2-70b # roleplay configuration
+    parameters:
+      density: 1
+      weight: 0.25
+merge_method: dare_ties
+base_model: tokyotech-llm/Swallow-70b-NVE-instruct-hf
+dtype: bfloat16
+name: Swallow-70b-NVE-RP-flavor
+---
+slices:
+  - sources:
+      - model: Swallow-70b-NVE-RP-base
+        layer_range: [0, 80]
+      - model: Swallow-70b-NVE-RP-flavor
+        layer_range: [0, 80]
+merge_method: slerp
+base_model: Swallow-70b-NVE-RP-base
+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 # fallback for rest of tensors
+dtype: bfloat16
+name: Swallow-70b-NVE-RP

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+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
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+    },
+    "2": {
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}