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--- |
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language: |
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- en |
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license: other |
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tags: |
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- AI |
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- ConversationalAI |
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pipeline_tag: conversational |
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inference: false |
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model-index: |
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- name: LLmRa-1.3B_V2 |
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results: |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: AI2 Reasoning Challenge (25-Shot) |
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type: ai2_arc |
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config: ARC-Challenge |
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split: test |
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args: |
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num_few_shot: 25 |
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metrics: |
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- type: acc_norm |
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value: 30.46 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=L-R/LLmRa-1.3B_V2 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: HellaSwag (10-Shot) |
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type: hellaswag |
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split: validation |
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args: |
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num_few_shot: 10 |
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metrics: |
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- type: acc_norm |
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value: 53.03 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=L-R/LLmRa-1.3B_V2 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: MMLU (5-Shot) |
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type: cais/mmlu |
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config: all |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 26.06 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=L-R/LLmRa-1.3B_V2 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: TruthfulQA (0-shot) |
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type: truthful_qa |
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config: multiple_choice |
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split: validation |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: mc2 |
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value: 36.46 |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=L-R/LLmRa-1.3B_V2 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: Winogrande (5-shot) |
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type: winogrande |
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config: winogrande_xl |
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split: validation |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 59.27 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=L-R/LLmRa-1.3B_V2 |
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name: Open LLM Leaderboard |
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- task: |
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type: text-generation |
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name: Text Generation |
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dataset: |
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name: GSM8k (5-shot) |
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type: gsm8k |
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config: main |
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split: test |
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args: |
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num_few_shot: 5 |
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metrics: |
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- type: acc |
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value: 0.0 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=L-R/LLmRa-1.3B_V2 |
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name: Open LLM Leaderboard |
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--- |
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<h1 style="text-align: center">LLmRa-1.3B-V2</h1> |
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<h2 style="text-align: center">A conversational Open Pre-trained Transformer Language Model fine-tune.</h2> |
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**LLmRa 1.3B-V2**, as a proof-of-concept fine-tune of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) optimized for dialogue. |
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**Disclaimer:** NSFW data was included in the fine-tuning of this model. Although SFW inputs will usually result in SFW outputs, you are advised to **chat at your own risk. This model is not suitable for use by minors.** |
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**Warning:** This model is **NOT** suitable for use by minors. **It will output X-rated content under certain circumstances.** |
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**Model Fine-Tuned on LLmRa-100K conversational dataset - small version** |
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--- |
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## Usage Format |
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To effectively utilize the model, follow this structured format for engaging text-based conversations: |
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**1. Initialization** |
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Here is how you can define the personality of the language model: |
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``` |
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<|system|>[Persona] |
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``` |
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- **Persona**: You can define a specific persona or context for the AI, but it's optional. It can be a character, a role, or just a style of interaction. |
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**2. AI Introduction** |
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``` |
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<|user|>[User input]<|model|> |
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``` |
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- Users can start the conversation by entering their message within `<|user|>` and closing with `<|model|>`. |
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--- |
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### Example Usage: |
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Here's an example of how to start a conversation with the AI: |
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``` |
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<|system|>I'm here to provide information and assistance on a wide range of topics. |
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<|model|>Hello! Welcome to our AI-powered assistant. How can I assist you today? |
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<|user|>Tell me about the history of artificial intelligence. |
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<|model|> |
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``` |
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Continue the conversation as needed. This structured format helps maintain a smooth and engaging interaction with the AI. |
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You are not required to include `User`, you can change it to your prefered name or leave it blank You may also add the AI name, example: |
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``` |
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<|user|>YourNameHere: Hello.<|model|>CharacterName: |
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``` |
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You can also use this instruct prompt example: |
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``` |
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<|system|>What is one plus one?<|model|> |
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``` |
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## Loading The Model |
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To use the model and interact with it, use the Python code below: |
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```Python |
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from transformers import (AutoModelForCausalLM, |
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AutoTokenizer, |
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pipeline, |
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) |
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model = AutoModelForCausalLM.from_pretrained('L-R/LLmRa-1.3B-V2') |
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tokenizer = AutoTokenizer.from_pretrained('L-R/LLmRa-1.3B-V2') |
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pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=100) |
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input_question = 'QUESTION HERE' |
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question_formatted = f'<|system|>{input_question}<|model|>' |
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result = pipe(question_formatted) |
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print(f"[model]: {result[0]['generated_text'][len(question_formatted):]}") |
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``` |
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## Known issues |
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Model doesn't some of the times follow instructions. |
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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_L-R__LLmRa-1.3B_V2) |
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| Metric |Value| |
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|---------------------------------|----:| |
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|Avg. |34.21| |
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|AI2 Reasoning Challenge (25-Shot)|30.46| |
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|HellaSwag (10-Shot) |53.03| |
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|MMLU (5-Shot) |26.06| |
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|TruthfulQA (0-shot) |36.46| |
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|Winogrande (5-shot) |59.27| |
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|GSM8k (5-shot) | 0.00| |
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