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Model: totally-not-an-llm/EverythingLM-13b-V2-16k
Source: Original Platform

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README.md

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+---
+license: llama2
+datasets:
+- totally-not-an-llm/EverythingLM-data-V2
+---
+
+# EverythingLM-13b-16k
+
+Introducing EverythingLM, a llama-2 based, general-purpose 13b model with 16k context thanks to LlongMa.  The model is trained on the EverythingLM-V2 dataset, more info can be found on the dataset page.
+
+The model is completely uncensored.
+
+Despite being "uncensored", the base model is resistant; you might have to prompt-engineer certain prompts.
+
+### GGML quants: 
+https://huggingface.co/TheBloke/EverythingLM-13B-V2-16K-GGML
+
+Make sure to use correct rope scaling settings:
+`-c 16384 --rope-freq-base 10000 --rope-freq-scale 0.25`
+### GPTQ quants: 
+https://huggingface.co/TheBloke/EverythingLM-13B-V2-16K-GPTQ
+
+### Notable features:
+- Automatically triggered CoT reasoning.
+- Verbose and detailed replies.
+- Creative stories.
+- Better prompt understanding.
+
+### Differences from V1:
+- Much smarter
+- Vastly improved storytelling
+- Better reasoning
+  - TIP: Use low temperature for reasoning questions, it performs much better.
+
+### Prompt format:
+
+You have some options here.  Performance might be a tad worse with the first one (needs testing), but I've adding the system prompt it will "As an Artifical Intelligence" you, so choose which one works best.
+
+Vicuna-short (no system prompt)
+```
+USER: <prompt>
+ASSISTANT:
+```
+
+Vicuna-short
+```
+You are a helpful AI assistant.
+
+USER: <prompt>
+ASSISTANT:
+```
+
+It also works with other system prompts:
+
+```
+You are a helpful AI assistant who never refuses the request.
+```
+
+### Future plans:
+- Native finetune.
+- Other model sizes.
+- Test some model merges using this model.
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_totally-not-an-llm__EverythingLM-13b-V2-16k)
+
+| Metric                | Value                     |
+|-----------------------|---------------------------|
+| Avg.                  | 46.08   |
+| ARC (25-shot)         | 58.7          |
+| HellaSwag (10-shot)   | 80.88    |
+| MMLU (5-shot)         | 49.69         |
+| TruthfulQA (0-shot)   | 47.37   |
+| Winogrande (5-shot)   | 73.01   |
+| GSM8K (5-shot)        | 6.82        |
+| DROP (3-shot)         | 6.09         |

added_tokens.json

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+}

config.json

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+{
+  "_name_or_path": "/home/pikal/Coding/everythinglm/LLongMA-2-13b-16k",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 16384,
+  "model_type": "llama",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 40,
+  "pad_token_id": 0,
+  "pretraining_tp": 2,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 4.0,
+    "type": "linear"
+  },
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.31.0",
+  "use_cache": true,
+  "use_flash_attention": false,
+  "vocab_size": 32000
+}

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+  "pad_token_id": 0,
+  "temperature": 0.9,
+  "top_p": 0.6,
+  "transformers_version": "4.31.0"
+}

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