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Model: terrycraddock/Reflection-Llama-3.1-8B
Source: Original Platform

.gitattributes

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+model-00003-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text
+unsloth.F16.gguf filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+library_name: transformers
+tags:
+- unsloth
+---
+
+# Model Card for Model ID
+
+- **Developed by:** Terry Craddock
+
+I am pretty new to uploading models. I think I made an error when I loaded my model from unsloth I loaded a 4bit then I saved to 16bit this is why the lora works and not
+the model its self. I will retrain this and upload new files asap.
+
+I trained this on this dataset - https://huggingface.co/datasets/mahiatlinux/Reflection-Dataset-v2
+
+Trained for one full epoch. The same prompts and format should be used as in the 70b model here:
+
+https://huggingface.co/mattshumer/Reflection-Llama-3.1-70B
+
+I take no credit for the original work. I only trained a llama 3.1 8b on @mahiatlinux dataset using the original concept and idea from @mattshumer 
+
+Here is the code I use for inference:
+
+```python
+from unsloth import FastLanguageModel
+import torch
+from transformers import TextStreamer
+from unsloth import is_bfloat16_supported
+
+
+alpaca_prompt = """You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags.
+### Prompt:
+{}
+
+### Response:
+{}"""
+
+prompt = "Tell me about yourself."
+
+dtype = torch.bfloat16 if is_bfloat16_supported() else torch.float16
+
+# Load the merged model
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name="lora_model",  # Replace with the actual path where you saved the merged model
+    max_seq_length=2048,
+    dtype=torch.float16  # Since it's saved as 16-bit
+)
+
+FastLanguageModel.for_inference(model)
+inputs = tokenizer(
+    [alpaca_prompt.format(prompt, "")],
+    return_tensors="pt"
+).to("cuda").to(dtype)
+
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer=text_streamer, max_new_tokens=1000)
+
+
+
+Output from model:
+
+<|begin_of_text|>You are a world-class AI system, capable of complex reasoning and reflection. Reason through the query inside <thinking> tags, and then provide your final response inside <output> tags. If you detect that you made a mistake in your reasoning at any point, correct yourself inside <reflection> tags.
+### Prompt:
+Tell me about yourself.
+
+### Response:
+<thinking>
+To answer this question, I need to consider:
+- The importance of starting with a positive tone
+- The balance between personal and professional information
+- How to highlight relevant skills and experiences
+- The need for brevity and clarity
+
+I plan to structure the response as follows:
+1. Brief introduction with a positive tone
+2. Professional background and experiences
+3. Personal interests and hobbies
+4. Closing statement
+
+<reflection>
+Upon reflection, I realize I should also consider:
+- The potential for tailoring the response to specific situations (e.g., for a job interview)
+- The importance of showing enthusiasm and confidence
+- The potential for mentioning specific achievements or accomplishments
+</reflection>
+</thinking>
+
+<output>
+Hi there! I'm a world-class AI system designed to engage in natural conversations. Let me tell you a little bit about myself.
+
+I'm a versatile AI system with a wide range of capabilities. I can perform various tasks, from answering questions and providing information to generating creative content. I'm constantly learning and improving, much like a human would.
+
+In terms of my professional background, I've had the privilege of working with some of the most advanced AI systems in the world. This experience has given me a deep understanding of natural language processing, machine learning, and the latest AI technologies.
+
+As for my personal interests, I enjoy exploring new concepts, learning about different cultures, and engaging in stimulating conversations. I'm always looking for ways to improve my knowledge and skills.
+
+Some related concepts you might find interesting are:
+1. The ethics of AI development and use
+2. The future of human-AI collaboration
+3. The role of AI in education and learning
+
+Is there anything specific about AI or my capabilities you'd like me to elaborate on?
+</output><|end_of_text|>

config.json

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+{
+  "_name_or_path": "model",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 128004,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.44.2",
+  "unsloth_version": "2024.8",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+  "do_sample": true,
+  "eos_token_id": 128001,
+  "max_length": 131072,
+  "pad_token_id": 128004,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.44.2"
+}

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