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Dolphin 2.7 Mixtral 8x7b by cognitivecomputations

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Dolphin 2.7 Mixtral 8x7b is an open-source language model by cognitivecomputations. Features: LLM, VRAM: 93.6GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.14.

  Autotrain compatible   Conversational Dataset:cognitivecomputations/... Dataset:cognitivecomputations/... Dataset:ise-uiuc/magicoder-evo... Dataset:ise-uiuc/magicoder-oss... Dataset:jondurbin/airoboros-2....   Dataset:ldjnr/capybara   Dataset:teknium/openhermes   En   Endpoints compatible   Instruct   Mixtral   Moe   Pytorch   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/cognitivecomputations/dolphin-2.7-mixtral-8x7b 

Dolphin 2.7 Mixtral 8x7b Benchmarks

LLME Score: 0.14325
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Dolphin 2.7 Mixtral 8x7b (cognitivecomputations/dolphin-2.7-mixtral-8x7b)
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Dolphin 2.7 Mixtral 8x7b Parameters and Internals

Model Type 
text generation, coding assistance
Additional Notes 
The model was retrained to fix performance issues. It is highly compliant and uncensored. Trust_remote_code is required.
Supported Languages 
en (proficient)
Training Details 
Data Sources:
cognitivecomputations/dolphin, jondurbin/airoboros-2.2.1, cognitivecomputations/dolphin-coder, teknium/openhermes, ise-uiuc/Magicoder-OSS-Instruct-75K, ise-uiuc/Magicoder-Evol-Instruct-110K, LDJnr/Capybara
Methodology:
qLoRA and Axolotl Prompt format using ChatML
Context Length:
16000
Training Time:
3 days
Hardware Used:
4x A100 GPUs
Input Output 
Input Format:
ChatML
Accepted Modalities:
text
Output Format:
text responses
Performance Tips:
The model is uncensored and highly compliant; it’s advised to have an alignment layer to control unethical requests.
LLM NameDolphin 2.7 Mixtral 8x7b
Repository 🤗https://huggingface.co/cognitivecomputations/dolphin-2.7-mixtral-8x7b 
Required VRAM93.6 GB
Updated2025-07-13
Maintainercognitivecomputations
Model Typemixtral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-19   5.0 GB: 2-of-19   5.0 GB: 3-of-19   4.9 GB: 4-of-19   5.0 GB: 5-of-19   5.0 GB: 6-of-19   4.9 GB: 7-of-19   5.0 GB: 8-of-19   5.0 GB: 9-of-19   4.9 GB: 10-of-19   5.0 GB: 11-of-19   5.0 GB: 12-of-19   5.0 GB: 13-of-19   4.9 GB: 14-of-19   5.0 GB: 15-of-19   5.0 GB: 16-of-19   4.9 GB: 17-of-19   5.0 GB: 18-of-19   4.2 GB: 19-of-19
Supported Languagesen
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16

Quantized Models of the Dolphin 2.7 Mixtral 8x7b

Model
Likes
Downloads
VRAM
Dolphin 2.7 Mixtral 8x7b GGUF147923715 GB
Dolphin 2.7 Mixtral 8x7b AWQ23367124 GB
Dolphin 2.7 Mixtral 8x7b GGUF551115 GB
Dolphin 2.7 Mixtral 8x7b GPTQ197823 GB

Best Alternatives to Dolphin 2.7 Mixtral 8x7b

Best Alternatives
Context / RAM
Downloads
Likes
...ixtral 8x22B Instruct V0.1 FP864K / 140.9 GB980
Dolphin 2.6 Mixtral 8x7b32K / 93.6 GB11285211
Dolphin 2.6 Mixtral 8x7b32K / 93.6 GB7859216
...eqlen 4096 Bs 4 Optimum 0 0 2332K /  GB70
...eqlen 4096 Bs 4 Optimum 0 0 2332K /  GB31
Empower Functions Medium32K / 93.6 GB71
Mixtral 8x7B Instruct V0.132K /  GB70
Dolphin 2.7 Mixtral 8x7b32K / 92.9 GB350
Dolphin 2.7 Mixtral 8x7b32K / 93.6 GB261169
...ral 8x7b Instruct V0.1 Int4 Ov32K / 0 GB244
Note: green Score (e.g. "73.2") means that the model is better than cognitivecomputations/dolphin-2.7-mixtral-8x7b.

Rank the Dolphin 2.7 Mixtral 8x7b 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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