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Openchat 3.5 1210 GPTQ by TheBloke

 »  All LLMs  »  TheBloke  »  Openchat 3.5 1210 GPTQ   URL Share it on

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  Arxiv:2212.10560   Arxiv:2303.08774   Arxiv:2309.11235   4-bit   Autotrain compatible Base model:openchat/openchat-3... Base model:quantized:openchat/...   C-rlft   Conversational Dataset:glaiveai/glaive-code-a...   Dataset:imone/openorca flan Dataset:kaist-ai/feedback-coll... Dataset:ldjnr/lesswrong-amplif...   Dataset:ldjnr/pure-dove   Dataset:ldjnr/verified-camel   Dataset:meta-math/metamathqa Dataset:openassistant/oasst to... Dataset:openchat/openchat shar...   Dataset:tiedong/goat   Dataset:tiger-lab/mathinstruct   Gptq   Mistral   Openchat   Quantized   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/TheBloke/openchat-3.5-1210-GPTQ 

Openchat 3.5 1210 GPTQ Benchmarks

LLME Score: 0.15276
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Openchat 3.5 1210 GPTQ (TheBloke/openchat-3.5-1210-GPTQ)

Openchat 3.5 1210 GPTQ Parameters and Internals

Model Type 
text-generation, chatbot
Use Cases 
Areas:
Coding, Chat, General Tasks, Mathematical Reasoning
Applications:
General AI assistant, Code generation, Mathematical problem solving, OpenAI API-compatible requests
Primary Use Cases:
Coding assistance, Conversational AI, Learning and education tools
Limitations:
May generate inaccurate information, Possibility of harmful or biased outputs
Considerations:
Users should verify outputs, especially critical information.
Additional Notes 
Experimental evaluator capabilities for feedback and scoring, aimed at promoting open-source models as evaluators.
Supported Languages 
English (High), Chinese (Low)
Training Details 
Data Sources:
openchat/openchat_sharegpt4_dataset, kaist-ai/Feedback-Collection, imone/OpenOrca_FLAN, LDJnr/LessWrong-Amplify-Instruct, LDJnr/Pure-Dove, LDJnr/Verified-Camel, tiedong/goat, glaiveai/glaive-code-assistant, meta-math/MetaMathQA, OpenAssistant/oasst_top1_2023-08-25, TIGER-Lab/MathInstruct
Methodology:
Trained with C-RLFT on a collection of publicly available high-quality instruction data
Context Length:
8192
Hardware Used:
Massed Compute
Model Architecture:
Mistral
Input Output 
Input Format:
Prompt with specified format: 'GPT4 Correct User: {prompt}<|end_of_turn|>GPT4 Correct Assistant:'
Accepted Modalities:
text
Output Format:
Generated textual response.
Performance Tips:
Make use of conversation templates to improve interaction quality.
LLM NameOpenchat 3.5 1210 GPTQ
Repository 🤗https://huggingface.co/TheBloke/openchat-3.5-1210-GPTQ 
Model NameOpenchat 3.5 1210
Model CreatorOpenChat
Base Model(s)  openchat/openchat-3.5-1210   openchat/openchat-3.5-1210
Model Size1.2b
Required VRAM4.2 GB
Updated2025-02-22
MaintainerTheBloke
Model Typemistral
Model Files  4.2 GB
GPTQ QuantizationYes
Quantization Typegptq
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length8192
Model Max Length8192
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32002
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/openchat-3.5-1210-GPTQ.

Rank the Openchat 3.5 1210 GPTQ Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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Release v20241227
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