初始化项目，由ModelHub XC社区提供模型
Model: Local-Novel-LLM-project/Ninja-v1 Source: Original Platform
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README.md
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---
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license: apache-2.0
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language:
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- en
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- ja
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tags:
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- finetuned
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library_name: transformers
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pipeline_tag: text-generation
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---
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<img src="./ninjalogo.svg" width="100%" height="20%" alt="">
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# Our Models
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- [Vecteus](https://huggingface.co/Local-Novel-LLM-project/Vecteus-v1)
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- [Ninja-v1](https://huggingface.co/Local-Novel-LLM-project/Ninja-v1)
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- [Ninja-v1-NSFW](https://huggingface.co/Local-Novel-LLM-project/Ninja-v1-NSFW)
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- [Ninja-v1-128k](https://huggingface.co/Local-Novel-LLM-project/Ninja-v1-128k)
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- [Ninja-v1-NSFW-128k](https://huggingface.co/Local-Novel-LLM-project/Ninja-v1-NSFW-128k)
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## Model Card for Ninja-v1.0
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The Mistral-7B--based Large Language Model (LLM) is an noveldataset fine-tuned version of the Mistral-7B-v0.1
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Ninja has the following changes compared to Mistral-7B-v0.1.
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- Achieving both high quality Japanese and English generation
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- Memory ability that does not forget even after long-context generation
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This model was created with the help of GPUs from the first LocalAI hackathon.
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We would like to take this opportunity to thank
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## List of Creation Methods
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- Chatvector for multiple models
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- Simple linear merging of result models
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- Domain and Sentence Enhancement with LORA
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- Context expansion
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## Instruction format
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Ninja adopts the prompt format from Vicuna and supports multi-turn conversation.
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The prompt should be as following:
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```
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USER: Hi ASSISTANT: Hello.</s>
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USER: Who are you?
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ASSISTANT: I am ninja.</s>
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```
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## Example prompts to improve (Japanese)
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- BAD: あなたは○○として振る舞います
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- GOOD: あなたは○○です
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- BAD: あなたは○○ができます
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- GOOD: あなたは○○をします
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## Performing inference
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "Local-Novel-LLM-project/Ninja-v1"
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new_tokens = 1024
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model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True, torch_dtype=torch.float16, attn_implementation="flash_attention_2", device_map="auto")
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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system_prompt = "あなたはプロの小説家です。\n小説を書いてください\n-------- "
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prompt = input("Enter a prompt: ")
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system_prompt += prompt + "\n-------- "
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model_inputs = tokenizer([system_prompt], return_tensors="pt").to("cuda")
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generated_ids = model.generate(**model_inputs, max_new_tokens=new_tokens, do_sample=True)
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print(tokenizer.batch_decode(generated_ids)[0])
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````
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## Merge recipe
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- WizardLM2 - mistralai/Mistral-7B-v0.1
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- Elizezen/Antler-7B - stabilityai/japanese-stablelm-instruct-gamma-7b
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- NTQAI/chatntq-ja-7b-v1.0
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The characteristics of each model are as follows.
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- WizardLM2: High quality multitasking model
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- Antler-7B: Model specialized for novel writing
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- NTQAI/chatntq-ja-7b-v1.0 High quality Japanese specialized model
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## Other points to keep in mind
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- The training data may be biased. Be careful with the generated sentences.
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- Memory usage may be large for long inferences.
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- If possible, we recommend inferring with llamacpp rather than Transformers.
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config.json
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{
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"_name_or_path": "NovelHacja/Wizardntq-ja-7B",
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"architectures": [
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"MistralForCausalLM"
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],
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 4096,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.39.3",
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"use_cache": true,
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"vocab_size": 32000
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}
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|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
44
tokenizer_config.json
Normal file
44
tokenizer_config.json
Normal file
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"add_bos_token": true,
|
||||
"add_eos_token": false,
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [],
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"padding_side": "left",
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": true
|
||||
}
|
||||
Reference in New Issue
Block a user