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Model: NousResearch/Nous-Hermes-llama-2-7b
Source: Original Platform

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README.md

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+---
+language:
+- en
+tags:
+- llama-2
+- self-instruct
+- distillation
+- synthetic instruction
+license:
+- mit
+new_version: NousResearch/Hermes-3-Llama-3.1-8B
+---
+
+# Model Card: Nous-Hermes-Llama2-7b
+
+Compute provided by our project sponsor Redmond AI, thank you! Follow RedmondAI on Twitter @RedmondAI.
+
+## Model Description
+
+Nous-Hermes-Llama2-7b is a state-of-the-art language model fine-tuned on over 300,000 instructions. This model was fine-tuned by Nous Research, with Teknium leading the fine tuning process and dataset curation, Redmond AI sponsoring the compute, and several other contributors.
+
+This Hermes model uses the exact same dataset as Hermes on Llama-1. This is to ensure consistency between the old Hermes and new, for anyone who wanted to keep Hermes as similar to the old one, just more capable.
+
+This model stands out for its long responses, lower hallucination rate, and absence of OpenAI censorship mechanisms. The fine-tuning process was performed with a 4096 sequence length on an 8x a100 80GB DGX machine.
+
+
+## Model Training
+
+The model was trained almost entirely on synthetic GPT-4 outputs. Curating high quality GPT-4 datasets enables incredibly high quality in knowledge, task completion, and style.
+
+This includes data from diverse sources such as GPTeacher, the general, roleplay v1&2, code instruct datasets, Nous Instruct & PDACTL (unpublished), and several others, detailed further below
+
+## Collaborators
+The model fine-tuning and the datasets were a collaboration of efforts and resources between Teknium, Karan4D, Emozilla, Huemin Art and Redmond AI. 
+  
+Special mention goes to @winglian for assisting in some of the training issues.
+
+Huge shoutout and acknowledgement is deserved for all the dataset creators who generously share their datasets openly. 
+
+Among the contributors of datasets:
+- GPTeacher was made available by Teknium
+- Wizard LM by nlpxucan
+- Nous Research Instruct Dataset was provided by Karan4D and HueminArt.  
+- GPT4-LLM and Unnatural Instructions were provided by Microsoft
+- Airoboros dataset by jondurbin
+- Camel-AI's domain expert datasets are from Camel-AI
+- CodeAlpaca dataset by Sahil 2801.
+
+If anyone was left out, please open a thread in the community tab.
+
+## Prompt Format
+
+The model follows the Alpaca prompt format:
+```
+### Instruction:
+<prompt>
+
+### Response:
+<leave a newline blank for model to respond>
+
+```
+
+or 
+
+```
+### Instruction:
+<prompt>
+
+### Input:
+<additional context>
+
+### Response:
+<leave a newline blank for model to respond>
+```
+
+GPT4All:
+```|    Task     |Version| Metric |Value |   |Stderr|
+|-------------|------:|--------|-----:|---|-----:|
+|arc_challenge|      0|acc     |0.4735|±  |0.0146|
+|             |       |acc_norm|0.5017|±  |0.0146|
+|arc_easy     |      0|acc     |0.7946|±  |0.0083|
+|             |       |acc_norm|0.7605|±  |0.0088|
+|boolq        |      1|acc     |0.8000|±  |0.0070|
+|hellaswag    |      0|acc     |0.5924|±  |0.0049|
+|             |       |acc_norm|0.7774|±  |0.0042|
+|openbookqa   |      0|acc     |0.3600|±  |0.0215|
+|             |       |acc_norm|0.4660|±  |0.0223|
+|piqa         |      0|acc     |0.7889|±  |0.0095|
+|             |       |acc_norm|0.7976|±  |0.0094|
+|winogrande   |      0|acc     |0.6993|±  |0.0129|
+Average: 0.686
+```  
+
+BigBench:
+```
+|                      Task                      |Version|       Metric        |Value |   |Stderr|
+|------------------------------------------------|------:|---------------------|-----:|---|-----:|
+|bigbench_causal_judgement                       |      0|multiple_choice_grade|0.5579|±  |0.0361|
+|bigbench_date_understanding                     |      0|multiple_choice_grade|0.6233|±  |0.0253|
+|bigbench_disambiguation_qa                      |      0|multiple_choice_grade|0.3062|±  |0.0288|
+|bigbench_geometric_shapes                       |      0|multiple_choice_grade|0.2006|±  |0.0212|
+|                                                |       |exact_str_match      |0.0000|±  |0.0000|
+|bigbench_logical_deduction_five_objects         |      0|multiple_choice_grade|0.2540|±  |0.0195|
+|bigbench_logical_deduction_seven_objects        |      0|multiple_choice_grade|0.1657|±  |0.0141|
+|bigbench_logical_deduction_three_objects        |      0|multiple_choice_grade|0.4067|±  |0.0284|
+|bigbench_movie_recommendation                   |      0|multiple_choice_grade|0.2780|±  |0.0201|
+|bigbench_navigate                               |      0|multiple_choice_grade|0.5000|±  |0.0158|
+|bigbench_reasoning_about_colored_objects        |      0|multiple_choice_grade|0.4405|±  |0.0111|
+|bigbench_ruin_names                             |      0|multiple_choice_grade|0.2701|±  |0.0210|
+|bigbench_salient_translation_error_detection    |      0|multiple_choice_grade|0.2034|±  |0.0127|
+|bigbench_snarks                                 |      0|multiple_choice_grade|0.5028|±  |0.0373|
+|bigbench_sports_understanding                   |      0|multiple_choice_grade|0.6136|±  |0.0155|
+|bigbench_temporal_sequences                     |      0|multiple_choice_grade|0.2720|±  |0.0141|
+|bigbench_tracking_shuffled_objects_five_objects |      0|multiple_choice_grade|0.1944|±  |0.0112|
+|bigbench_tracking_shuffled_objects_seven_objects|      0|multiple_choice_grade|0.1497|±  |0.0085|
+|bigbench_tracking_shuffled_objects_three_objects|      0|multiple_choice_grade|0.4067|±  |0.0284|
+Average: 0.3525
+```  
+
+AGIEval
+```  
+|             Task             |Version| Metric |Value |   |Stderr|
+|------------------------------|------:|--------|-----:|---|-----:|
+|agieval_aqua_rat              |      0|acc     |0.2520|±  |0.0273|
+|                              |       |acc_norm|0.2402|±  |0.0269|
+|agieval_logiqa_en             |      0|acc     |0.2796|±  |0.0176|
+|                              |       |acc_norm|0.3241|±  |0.0184|
+|agieval_lsat_ar               |      0|acc     |0.2478|±  |0.0285|
+|                              |       |acc_norm|0.2348|±  |0.0280|
+|agieval_lsat_lr               |      0|acc     |0.2843|±  |0.0200|
+|                              |       |acc_norm|0.2765|±  |0.0198|
+|agieval_lsat_rc               |      0|acc     |0.3271|±  |0.0287|
+|                              |       |acc_norm|0.3011|±  |0.0280|
+|agieval_sat_en                |      0|acc     |0.4660|±  |0.0348|
+|                              |       |acc_norm|0.4223|±  |0.0345|
+|agieval_sat_en_without_passage|      0|acc     |0.3738|±  |0.0338|
+|                              |       |acc_norm|0.3447|±  |0.0332|
+|agieval_sat_math              |      0|acc     |0.2500|±  |0.0293|
+|                              |       |acc_norm|0.2364|±  |0.0287|
+Average: 0.2975
+```  
+
+## Benchmark Results
+
+
+
+
+## Resources for Applied Use Cases:
+For an example of a back and forth chatbot using huggingface transformers and discord, check out: https://github.com/teknium1/alpaca-discord  
+For an example of a roleplaying discord chatbot, check out this: https://github.com/teknium1/alpaca-roleplay-discordbot  
+
+LM Studio is a good choice for a chat interface that supports GGML versions (to come)
+
+## Future Plans
+We plan to continue to iterate on both more high quality data, and new data filtering techniques to eliminate lower quality data going forward. 
+
+## Model Usage
+The model is available for download on Hugging Face. It is suitable for a wide range of language tasks, from generating creative text to understanding and following complex instructions.

added_tokens.json

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config.json

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+  "_name_or_path": "output/hermes-llama2-4k/checkpoint-2259",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
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+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.32.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

configuration.json

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generation_config.json

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+  "temperature": 0.9,
+  "top_p": 0.6,
+  "transformers_version": "4.32.0.dev0"
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special_tokens_map.json

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tokenizer_config.json

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