Duplicate from Replete-AI/Replete-Coder-Llama3-8B

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README.md

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+---
+license: other
+license_name: llama-3
+license_link: https://llama.meta.com/llama3/license/
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+datasets:
+- Replete-AI/code_bagel_hermes-2.5
+- Replete-AI/code_bagel
+- Replete-AI/OpenHermes-2.5-Uncensored
+- teknium/OpenHermes-2.5
+- layoric/tiny-codes-alpaca
+- glaiveai/glaive-code-assistant-v3
+- ajibawa-2023/Code-290k-ShareGPT
+- TIGER-Lab/MathInstruct
+- chargoddard/commitpack-ft-instruct-rated
+- iamturun/code_instructions_120k_alpaca
+- ise-uiuc/Magicoder-Evol-Instruct-110K
+- cognitivecomputations/dolphin-coder
+- nickrosh/Evol-Instruct-Code-80k-v1
+- coseal/CodeUltraFeedback_binarized
+- glaiveai/glaive-function-calling-v2
+- CyberNative/Code_Vulnerability_Security_DPO
+- jondurbin/airoboros-2.2
+- camel-ai
+- lmsys/lmsys-chat-1m
+- CollectiveCognition/chats-data-2023-09-22
+- CoT-Alpaca-GPT4
+- WizardLM/WizardLM_evol_instruct_70k
+- WizardLM/WizardLM_evol_instruct_V2_196k
+- teknium/GPT4-LLM-Cleaned
+- GPTeacher
+- OpenGPT
+- meta-math/MetaMathQA
+- Open-Orca/SlimOrca
+- garage-bAInd/Open-Platypus
+- anon8231489123/ShareGPT_Vicuna_unfiltered
+- Unnatural-Instructions-GPT4
+model-index:
+- name: Replete-Coder-llama3-8b
+  results:
+  - task:
+      name: HumanEval
+      type: text-generation
+    dataset:
+      type: openai_humaneval
+      name: HumanEval
+    metrics:
+    - name: pass@1
+      type: pass@1
+      value: .64683835842678326
+      verified: True
+  - task:
+      name: AI2 Reasoning Challenge
+      type: text-generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: accuracy
+      value: 
+      name: normalized accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: accuracy
+      value: 
+      name: normalized accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: accuracy
+      value: 
+      name: accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: multiple_choice_accuracy
+      value: 
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: accuracy
+      value: 
+      name: accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+  - task:
+      name: Text Generation
+      type: text-generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: accuracy
+      value: 
+      name: accuracy
+    source:
+      url: https://www.placeholderurl.com
+      name: Open LLM Leaderboard
+---
+# Replete-Coder-llama3-8b
+Finetuned by: Rombodawg
+### More than just a coding model!
+Although Replete-Coder has amazing coding capabilities, its trained on vaste amount of non-coding data, fully cleaned and uncensored. Dont just use it for coding, use it for all your needs! We are truly trying to make the GPT killer!
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/-0dERC793D9XeFsJ9uHbx.png)
+
+Thank you to TensorDock for sponsoring Replete-Coder-llama3-8b and Replete-Coder-Qwen2-1.5b
+you can check out their website for cloud compute rental below. 
+- https://tensordock.com
+__________________________________________________________________________________________________
+Replete-Coder-llama3-8b is a general purpose model that is specially trained in coding in over 100 coding languages. The data used to train the model contains 25% non-code instruction data and 75% coding instruction data totaling up to 3.9 million lines, roughly 1 billion tokens, or 7.27gb of instruct data. The data used to train this model was 100% uncensored, then fully deduplicated, before training happened.
+
+The Replete-Coder models (including Replete-Coder-llama3-8b and Replete-Coder-Qwen2-1.5b) feature the following:
+
+- Advanced coding capabilities in over 100 coding languages
+- Advanced code translation (between languages)
+- Security and vulnerability prevention related coding capabilities
+- General purpose use
+- Uncensored use
+- Function calling
+- Advanced math use
+- Use on low end (8b) and mobile (1.5b) platforms
+
+Notice: Replete-Coder series of models are fine-tuned on a context window of 8192 tokens. Performance past this context window is not guaranteed.
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/642cc1c253e76b4c2286c58e/C-zxpY5n8KuzQeocmhk0g.png)
+__________________________________________________________________________________________________
+You can find the 25% non-coding instruction below:
+
+-  https://huggingface.co/datasets/Replete-AI/OpenHermes-2.5-Uncensored
+
+And the 75% coding specific instruction data below:
+
+- https://huggingface.co/datasets/Replete-AI/code_bagel
+
+These two datasets were combined to create the final dataset for training, which is linked below:
+
+- https://huggingface.co/datasets/Replete-AI/code_bagel_hermes-2.5
+__________________________________________________________________________________________________
+## Prompt Template: Custom Alpaca
+```
+### System:
+{}
+
+### Instruction:
+{}
+
+### Response:
+{}
+```
+Note: The system prompt varies in training data, but the most commonly used one is:
+```
+Below is an instruction that describes a task, Write a response that appropriately completes the request.
+```
+End token:
+```
+<|endoftext|>
+```
+__________________________________________________________________________________________________
+Thank you to the community for your contributions to the Replete-AI/code_bagel_hermes-2.5 dataset. Without the participation of so many members making their datasets free and open source for any to use, this amazing AI model wouldn't be possible.
+
+Extra special thanks to Teknium for the Open-Hermes-2.5 dataset and jondurbin for the bagel dataset and the naming idea for the code_bagel series of datasets. You can find both of their huggingface accounts linked below:
+
+- https://huggingface.co/teknium
+- https://huggingface.co/jondurbin
+
+Another special thanks to unsloth for being the main method of training for Replete-Coder. Bellow you can find their github, as well as the special Replete-Ai secret sause (Unsloth + Qlora + Galore) colab code document that was used to train this model.
+
+- https://github.com/unslothai/unsloth
+- https://colab.research.google.com/drive/1VAaxMQJN9-78WLsPU0GWg5tEkasXoTP9?usp=sharing
+__________________________________________________________________________________________________
+## Join the Replete-Ai discord! We are a great and Loving community!
+
+- https://discord.gg/ZZbnsmVnjD

config.json

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+{
+  "_name_or_path": "NousResearch/Meta-Llama-3-8B",
+  "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": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 128255,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.2",
+  "unsloth_version": "2024.6",
+  "use_cache": true,
+  "vocab_size": 128256
+}

generation_config.json

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+{
+  "bos_token_id": 128000,
+  "do_sample": true,
+  "eos_token_id": 128001,
+  "max_length": 4096,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.41.2"
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special_tokens_map.json

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+  },
+  "bos_token": "<|begin_of_text|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|end_of_text|>",
+  "chat_template": "{% if not add_generation_prompt is defined %}\n{% set add_generation_prompt = false %}\n{% endif %}\n{%- set ns = namespace(found=false) -%}\n{%- for message in messages -%}\n    {%- if message['role'] == 'system' -%}\n        {%- set ns.found = true -%}\n    {%- endif -%}\n{%- endfor -%}\n{{bos_token}}{%- if not ns.found -%}\n{{'### System: Below is an instruction that describes a task, Write a response that appropriately completes the request.\\n'}}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message['role'] == 'system' %}\n{{ message['content'] }}\n    {%- else %}\n        {%- if message['role'] == 'user' %}\n{{'### Instruction:\\n' + message['content'] + '\\n'}}\n        {%- else %}\n{{'### Response:\\n' + message['content'] + '\\n<|endoftext|>\\n'}}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{% if add_generation_prompt %}\n{{'### Response:'}}\n{% endif %}",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 8192,
+  "pad_token": "<|reserved_special_token_250|>",
+  "padding_side": "left",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}