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@@ -7,4 +7,87 @@ base_model:
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  pipeline_tag: question-answering
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  tags:
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  - art
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  pipeline_tag: question-answering
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  tags:
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  - art
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+ ---
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+ # tinygoop-1
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+
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+ ## Model Description
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+
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+ A fine-tuned version of TinyLlama-1.1B-Chat with room temp iq -> quantized to 4 bits and trained on copypastas
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+
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+ ## Intended Use
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+
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+ - **Primary Use:** Not much, it barely can hold a conversation
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+ - **Secondary Uses:** brainrot generation, funny responses
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+ - **Out-of-scope:** Professional/business applications, factual question answering, safety-critical applications
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+
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+ ---
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+
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+ ## Training Data
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+
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+ **Sources:**
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+ - 334,165 copypastas
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+ - The script from the television show "House"
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+
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+ ### Hardware used in training
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+
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+ - **GPU:** NVIDIA GeForce RTX 4090
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+ - **CUDA:** 12.1
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+ - **Framework:** PyTorch 2.5.1+cu121
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+ - **Transformers:** Latest
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+ - **PEFT:** Latest
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+ - **BitsAndBytes:** 4-bit quantization
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+
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+ ---
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+
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+ ### Basic Usage
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+
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+ ```python
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+ import torch
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+
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+ model_id = "S-teven/tinygoop-1"
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+
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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=torch.float16,
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+ device_map="auto"
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+ )
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+
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+ prompt = "hey"
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+ inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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+
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+ outputs = model.generate(
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+ **inputs,
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+ max_new_tokens=256,
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+ do_sample=True,
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+ temperature=1.2,
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+ top_p=0.95,
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+ repetition_penalty=1.05
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+ )
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+
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+ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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+ ```
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+
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+ ### Hardware Requirements
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+
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+ | Precision | VRAM Required | Hardware |
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+ |-----------|---------------|----------|
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+ | 4-bit Quantized | ~800MB | Any modern GPU |
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+ | CPU (FP32) | ~4GB RAM | Modern CPU (slow) |
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+
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+ ---
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+
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+ ## Limitations & Biases
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+
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+ **Content Warning:** This model was trained on copypasta data and may generate:
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+ - Offensive or inappropriate content
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+ - Nonsensical or chaotic responses
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+ - Biases present in online communities
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+
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+ **Not suitable for:**
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+ - Most things
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+ - Professional or business use
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+ - Educational applications
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+ - Factual information retrieval
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+ - Content requiring safety guarantees