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Model: EpistemeAI/Fireball-R1-Llama-3.1-8B-Medical-COT Source: Original Platform
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README.md
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README.md
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---
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base_model: EpistemeAI/Fireball-R1-Llama-3.1-8B
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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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license: apache-2.0
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language:
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- en
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datasets:
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- FreedomIntelligence/medical-o1-reasoning-SFT
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---
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## Model Information
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# EpistemeAI/Fireball-R1-Llama-3.1-8B-Medical-COT
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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. This is supervised fine tuned with medical chain of thought
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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-Medical-COT")
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model = AutoModelForCausalLM.from_pretrained("EpistemeAI/Fireball-R1-Llama-3.1-8B-Medical-COT")
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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-Medical-COT")
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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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# 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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- 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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# Uploaded model
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- **Developed by:** EpistemeAI
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- **License:** apache-2.0
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- **Finetuned from model :** EpistemeAI/Fireball-R1-Llama-3.1-8B
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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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config.json
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"_name_or_path": "EpistemeAI/Fireball-R1-Llama-3.1-8B",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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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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"pad_token_id": 128004,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.48.3",
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"unsloth_fixed": true,
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"unsloth_version": "2025.2.12",
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"use_cache": true,
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"vocab_size": 128256
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}
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"temperature": 0.6,
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"top_p": 0.95,
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"transformers_version": "4.48.3"
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}
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3
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Normal file
3
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Normal file
@@ -0,0 +1,3 @@
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||||
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||||
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2072
tokenizer_config.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user