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QCammel 70 X by augtoma

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QCammel 70 X is an open-source language model by augtoma. Features: LLM, VRAM: 138GB, Context: 4K, License: other, LLM Explorer Score: 0.11, Arc: 68.3, HellaSwag: 87.9, MMLU: 70.2, GSM8K: 29.7.

  Arxiv:2302.70971   Arxiv:2305.12031   Arxiv:2305.14314   En   Llama   Llama2   Pytorch   Qcammel-70   Region:us   Sharded
Model Card on HF 🤗: https://huggingface.co/augtoma/qCammel-70-x 

QCammel 70 X Benchmarks

ARC: 68.34 vs 96.7 (so35)-29.3%
HellaSwag: 87.87 vs 95.3 (gpt4)-7.8%
MMLU: 70.18 vs 88.3 (so35)-20.5%
GSM8K: 29.72 vs 96.4 (so35)-69.2%
LLME Score: 0.10911
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
QCammel 70 X (augtoma/qCammel-70-x)
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QCammel 70 X Parameters and Internals

Model Type 
text generation
Use Cases 
Applications:
academic medical knowledge, instruction-following capabilities
Training Details 
Data Volume:
15,000 instructions
Methodology:
Distilled dataset using QLoRA
Model Architecture:
Auto-regressive language model using a decoder only transformer architecture.
Input Output 
Input Format:
text only
Output Format:
text only
LLM NameQCammel 70 X
Repository 🤗https://huggingface.co/augtoma/qCammel-70-x 
Required VRAM138 GB
Updated2026-05-19
Maintaineraugtoma
Model Typellama
Model Files  9.8 GB: 1-of-15   9.8 GB: 2-of-15   10.0 GB: 3-of-15   9.8 GB: 4-of-15   9.8 GB: 5-of-15   9.8 GB: 6-of-15   10.0 GB: 7-of-15   9.8 GB: 8-of-15   9.8 GB: 9-of-15   9.8 GB: 10-of-15   10.0 GB: 11-of-15   9.8 GB: 12-of-15   9.8 GB: 13-of-15   9.5 GB: 14-of-15   0.5 GB: 15-of-15
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length4096
Model Max Length4096
Transformers Version4.32.0.dev0
Tokenizer ClassLlamaTokenizer
Beginning of Sentence Token<s>
End of Sentence Token</s>
Unk Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

Quantized Models of the QCammel 70 X

Model
Likes
Downloads
VRAM
QCammel 70 X GGUF494529 GB
QCammel 70 X AWQ11536 GB
QCammel 70 X GPTQ22735 GB
QCammel 70 X GGML3928 GB

Best Alternatives to QCammel 70 X

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LWM Text 512K512K / 13.5 GB132
LWM Text Chat 512K512K / 13.5 GB112
LWM Text 256K256K / 13.5 GB123
LWM Text Chat 256K256K / 13.5 GB103
Pallas 0.5 LASER 0.1195K / 68.9 GB10402
Veena128K / 7.6 GB3406232
SnorTTS Indic V0128K / 9.5 GB85921
Llama 3.1 Medprm Reward V1.0128K / 16.1 GB66716
Orpheus AUS128K /  GB50
Finetuning Health Ci128K / 6.5 GB32
Note: green Score (e.g. "73.2") means that the model is better than augtoma/qCammel-70-x.

Rank the QCammel 70 X 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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