Amber By LLM360: Benchmarks, Features and Detailed Analysis. Insights on Amber.

Arxiv:2312.06550 Autotrain compatible En Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/LLM360/Amber

Amber Benchmarks

ARC: 40.96 vs 96.7 (so35)^-57.6%

HellaSwag: 73.79 vs 95.3 (gpt4)^-22.6%

MMLU: 26.84 vs 88.3 (so35)^-69.6%

TruthfulQA: 33.56 vs 59 (gpt4)^-43.1%

WinoGrande: 67.88 vs 87.5 (gpt4)^-22.4%

GSM8K: 2.81 vs 96.4 (so35)^-97.1%

LLME Score: 0.21987

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Amber Parameters and Internals

Model Type

Language model, text generation

Use Cases

Areas:

Research, Commercial applications

Limitations:

Not a SOTA model

Considerations:

Amber is released to make LLM training knowledge accessible to all.

Additional Notes

360 checkpoints available. To download other checkpoints, change the branch from 'main' to the checkpoint you want.

Supported Languages

English (NLP)

Training Details

Data Sources:

Arxiv, Book, C4, Refined-Web, StarCoder, StackExchange, Wikipedia

Data Volume:

1259.13 Billion tokens

Methodology:

Same architecture as LLaMA

Context Length:

2048

Model Architecture:

LLaMA architecture

Input Output

Accepted Modalities:

text

LLM Name	Amber
Repository 🤗	https://huggingface.co/LLM360/Amber
Model Size	6.7b
Required VRAM	13.5 GB
Updated	2025-02-22
Maintainer	LLM360
Model Type	llama
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 3.6 GB: 3-of-3
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the Amber

Model	Likes	Downloads	VRAM
Amber AWQ	1	80	3 GB
Amber GGUF	1	43	2 GB
Amber GPTQ	1	20	3 GB

Best Alternatives to Amber

Best Alternatives	Context / RAM	Downloads
Gptnoise37	128K / 13.5 GB	67
Phi 4 RRStock	16K / 7.7 GB	66
...s Coder6.7b Reflct Adamw Iter2	16K / 13.5 GB	480
...s Coder6.7b Reflct Adamw Iter1	16K / 13.5 GB	475
...ir8 Ds Coder6.7b Rmsprop Iter4	16K / 13.5 GB	183
...s Coder6.7b Reflct Adamw Iter3	16K / 13.5 GB	430
...ir8 Ds Coder6.7b Rmsprop Iter2	16K / 13.5 GB	183
Ds Coder6.7b Adamw Iter5	16K / 13.5 GB	405
...ir8 Ds Coder6.7b Rmsprop Iter3	16K / 13.5 GB	165
...s Coder6.7b Reflct Adamw Iter4	16K / 13.5 GB	273

Note: green Score (e.g. "73.2") means that the model is better than LLM360/Amber.

Rank the Amber 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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Original data from HuggingFace, OpenCompass and various public git repos.

Release v20241227

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