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Model: duliadotio/dulia-13b-8k-alpha Source: Original Platform
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README.md
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---
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license: llama2
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datasets:
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- shahules786/orca-chat
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- ehartford/dolphin
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language:
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- en
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library_name: transformers
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tags:
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- dulia
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- duliadotio
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- llama-8k
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- llama2
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---
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# Dulia 13B 8K (Alpha) (09082023)
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## Model Description
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Dulia 13B is an 8K context size on a long-conversation chat model based on Dolphin dataset ([Dolphin](https://huggingface.co/datasets/ehartford/dolphin)) and ([Chat](https://huggingface.co/datasets/shahules786/orca-chat)).
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It is trained using ([OpenAssistant SFT Trainer](https://github.com/LAION-AI/Open-Assistant/blob/main/model/model_training/trainer_sft.py)).
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## Usage
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```sh
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pip install -q transformers accelerate sentencepiece scipy torch
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```
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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# Check for the bfloat16 support. T4 does not support bfloat16
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dtype = torch.bfloat16 if torch.cuda.get_device_capability()[0] == 8 else torch.float16
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model_id = "duliadotio/dulia-13b-8k-alpha"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id
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torch_dtype=dtype,
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low_cpu_mem_usage=True,
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device_map="cuda"
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)
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system_message = "Dulia AI is a helpful and honest assistant designed by Dulia Inc. Take a step by step approach to answer user's query. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature. If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information."
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system_prompt = f"<|system|>{system_message}</s>"
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def infer(user_prompt, history = "", skip_special_tokens=False):
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prompt = ""
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if history == "":
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prompt += system_prompt
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prompt += history + f"<|prompter|>{user_prompt}</s><|assistant|>"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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output = model.generate(**inputs, do_sample=True, top_p=0.95, top_k=0, max_new_tokens=512)
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return tokenizer.decode(output[0], skip_special_tokens)
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user_prompt = "What is your name?"
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# This is the first message so, we don't have to pass the history.
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response = infer(user_prompt)
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user_prompt = "Can you write me an email?"
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response = infer(user_prompt, response)
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```
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## Long context (RoPE Scaling)
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This model is fine-tuned with a context size of 8192 tokens using linear scaling of RoPE embeddings.
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## Conversation Template
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The model is trained on OpenAssistant Chat Prompt.
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```
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<|system|>system message</s><|prompter|>user prompt</s><|assistant|>
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```
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For multi-turn conversations use:
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```
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<|system|>system message</s><|prompter|>User Question 1</s><|assistant|>Answer 1</s><|prompter|>User Question 2</s><|assistant|>
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```
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# Ethical Considerations and Limitations
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Dulia is a new technology and based on LLAMA 2 that carries risks with use. Testing conducted to date has been in English, and has not covered, nor could it cover all scenarios. For these reasons, as with all LLMs, Dulia's potential outputs cannot be predicted in advance, and the model may in some instances produce inaccurate, biased or other objectionable responses to user prompts. Therefore, before deploying any applications, developers should perform safety testing and tuning tailored to their specific applications of the model.
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Please see the Responsible Use Guide available at https://ai.meta.com/llama/responsible-use-guide/
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# License
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- Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
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- Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the [Acceptable Use Policy](https://ai.meta.com/llama/use-policy) for the Llama Materials.
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_duliadotio__dulia-13b-8k-alpha)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 49.67 |
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| ARC (25-shot) | 60.67 |
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| HellaSwag (10-shot) | 82.0 |
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| MMLU (5-shot) | 56.87 |
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| TruthfulQA (0-shot) | 42.59 |
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| Winogrande (5-shot) | 77.19 |
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| GSM8K (5-shot) | 10.69 |
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| DROP (3-shot) | 17.72 |
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config.json
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"_name_or_path": "model/dulia-13b-orca",
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"architectures": [
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"LlamaForCausalLM"
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"factor": 2.0,
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"use_cache": true,
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"vocab_size": 32016
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}
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26
special_tokens_map.json
Normal file
26
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Normal file
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|
||||
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||||
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|
||||
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||||
93445
tokenizer.json
Normal file
93445
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
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Normal file
3
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||||
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32
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Normal file
32
tokenizer_config.json
Normal file
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|
||||
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||||
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},
|
||||
"legacy": false,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": {
|
||||
"__type": "AddedToken",
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user