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--- |
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language: |
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- en |
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license: llama3.1 |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- llama |
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- trl |
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base_model: unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit |
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model-index: |
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- name: Fireball-R1-Llama-3.1-8B |
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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: IFEval (0-Shot) |
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type: HuggingFaceH4/ifeval |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: inst_level_strict_acc and prompt_level_strict_acc |
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value: 44.27 |
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name: strict accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=EpistemeAI/Fireball-R1-Llama-3.1-8B |
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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: BBH (3-Shot) |
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type: BBH |
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args: |
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num_few_shot: 3 |
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metrics: |
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- type: acc_norm |
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value: 10.27 |
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name: normalized accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=EpistemeAI/Fireball-R1-Llama-3.1-8B |
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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: MATH Lvl 5 (4-Shot) |
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type: hendrycks/competition_math |
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args: |
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num_few_shot: 4 |
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metrics: |
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- type: exact_match |
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value: 31.12 |
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name: exact match |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=EpistemeAI/Fireball-R1-Llama-3.1-8B |
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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: GPQA (0-shot) |
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type: Idavidrein/gpqa |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 0.0 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=EpistemeAI/Fireball-R1-Llama-3.1-8B |
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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: MuSR (0-shot) |
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type: TAUR-Lab/MuSR |
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args: |
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num_few_shot: 0 |
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metrics: |
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- type: acc_norm |
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value: 1.43 |
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name: acc_norm |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=EpistemeAI/Fireball-R1-Llama-3.1-8B |
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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-PRO (5-shot) |
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type: TIGER-Lab/MMLU-Pro |
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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: 1.28 |
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name: accuracy |
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source: |
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url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=EpistemeAI/Fireball-R1-Llama-3.1-8B |
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name: Open LLM Leaderboard |
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--- |
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**Upgrade** version: [EpistemeAI/Fireball-R1-Llama-3.1-8B-Medical-COT](https://huggingface.co/EpistemeAI/Fireball-R1-Llama-3.1-8B-Medical-COT) |
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## Model Information |
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# Fireball-R1-LLama-3.1-8B |
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This is a state-of-the-art language model optimized for **neutrality**, **STEM proficiency**, and **ethical alignment**. Fine-tuned Deepseek-R1-distill-llama-8b-unsloth-bnb-4bit for science, chemistry, and mathematics with reduced cultural/political bias. |
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This large language model is open source. |
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--- |
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## Table of Contents |
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- [Features](#features) |
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- [Installation](#installation) |
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- [Usage](#usage) |
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- [Training Details](#training-details) |
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- [Ethical Considerations](#ethical-considerations) |
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- [License](#license) |
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- [Citation](#citation) |
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- [Contact](#contact) |
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--- |
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## Features |
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- **Neutral Worldview**: Minimizes political/cultural bias via globally diverse training data and human feedback. |
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- **STEM Specialization**: Enhanced performance in: |
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- **Chemistry**: Reaction mechanisms, periodic trends, spectroscopy. |
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- **Mathematics**: Equation solving, proofs, calculus. |
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- **General Science**: Hypothesis generation, research summarization. |
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- **Ethical Guardrails**: Filters sensitive content and flags uncertain outputs. |
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--- |
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## Installation |
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```bash |
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pip install transformers torch |
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pip install accelerate |
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pip install -U transformers |
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``` |
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### Basic Inference |
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```bash |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("EpistemeAI/Fireball-R1-Llama-3.1-8B") |
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model = AutoModelForCausalLM.from_pretrained("EpistemeAI/Fireball-R1-Llama-3.1-8B") |
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prompt = "Calculate the molar mass of sulfuric acid (H₂SO₄)." |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate(**inputs, max_length=200) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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##advance inference |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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# Load the tokenizer |
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tokenizer = AutoTokenizer.from_pretrained("EpistemeAI/Fireball-R1-Llama-3.1-8B") |
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# Load the model in 8-bit precision using bitsandbytes (requires a CUDA GPU) |
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model = AutoModelForCausalLM.from_pretrained( |
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"EpistemeAI/Fireball-R1-Llama-3.1-8B", |
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load_in_8bit=True, # Enable 8-bit loading to reduce memory usage |
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device_map="auto" # Automatically map model layers to the available device(s) |
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) |
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# Define the system prompt and the user prompt |
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system_prompt = "You are a highly knowledgeable assistant with expertise in chemistry and physics. <think>" |
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user_prompt = "Calculate the molar mass of sulfuric acid (H₂SO₄)." |
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# Combine the system prompt with the user prompt. The format here follows a common convention for chat-like interactions. |
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full_prompt = f"System: {system_prompt}\nUser: {user_prompt}\nAssistant:" |
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# Tokenize the combined prompt and move the inputs to the GPU |
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inputs = tokenizer(full_prompt, return_tensors="pt").to("cuda") |
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# Generate output text from the model |
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outputs = model.generate(**inputs, max_length=12200) |
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# Decode and print the result, skipping special tokens |
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result = tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(result) |
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``` |
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### Recommended Parameters |
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```bash |
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outputs = model.generate( |
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**inputs, |
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max_length=300, |
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temperature=0.7, |
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top_p=0.95, |
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repetition_penalty=1.2 |
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) |
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``` |
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# Uploaded model |
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- **Developed by:** EpistemeAI |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/deepseek-r1-distill-llama-8b-unsloth-bnb-4bit |
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# Ethical Considerations |
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Do Not Use For: |
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- Medical/legal advice without expert oversight. |
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- Generating partisan or culturally insensitive content. |
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## Limitations: |
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- May occasionally produce plausible but incorrect scientific explanations. |
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- Not fully immune to subtle biases. |
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## Thank you |
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We appreciate the companies as following: Unsloth, Meta and Deepseek. |
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## License |
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This model is licensed under [apache-2.0] - see LICENSE for details. |
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## Citation |
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``` |
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@misc{Fireball-R1-Llama-3.1-8B, |
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author = {EpistemeAI}, |
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title = {Fireball-R1-8B: A Neutral, Science-Optimized Language Model}, |
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year = {2025}, |
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url = {https://huggingface.co/EpistemeAI/Fireball-R1-Llama-3.1-8B} |
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} |
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``` |
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For support or feedback: contact us at episteme.ai@proton.me |
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This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library. |
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) |
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/EpistemeAI__Fireball-R1-Llama-3.1-8B-details) |
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| Metric |Value| |
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|-------------------|----:| |
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|Avg. |14.73| |
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|IFEval (0-Shot) |44.27| |
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|BBH (3-Shot) |10.27| |
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|MATH Lvl 5 (4-Shot)|31.12| |
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|GPQA (0-shot) | 0.00| |
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|MuSR (0-shot) | 1.43| |
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|MMLU-PRO (5-shot) | 1.28| |
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