What are the hardware requirements for Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747?

Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747 requires approximately 7.3 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Where can I download or evaluate Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747?

Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747 by Finnish-NLP — VRAM 7.3GB, 2K context

Name: Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747
Author: Finnish-NLP

Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747 is an open-source language model by Finnish-NLP. Features: 3.6b LLM, VRAM: 7.3GB, Context: 2K, Merged, LLM Explorer Score: 0.13.

Merged Model Arxiv:1910.09700 Autotrain compatible Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Finnish-NLP/sft-hf_hf_2024_07_14_13_32_35_checkpoint_1314_dpo-checkpoint-747

Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747 Parameters and Internals

LLM Name	Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747
Repository 🤗	https://huggingface.co/Finnish-NLP/sft-hf_hf_2024_07_14_13_32_35_checkpoint_1314_dpo-checkpoint-747
Merged Model	Yes
Model Size	3.6b
Required VRAM	7.3 GB
Updated	2024-08-11
Maintainer	Finnish-NLP
Model Type	llama
Model Files	5.0 GB: 1-of-2 2.3 GB: 2-of-2
Model Architecture	LlamaForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.41.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<PAD>
Vocabulary Size	64257
Torch Data Type	float16

Rank the Sft Hf Hf 2024 07 14 13 32 35 Checkpoint 1314 DPO Checkpoint 747 capabilities

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

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Note: green Score (e.g. "73.2") means that the model is better than Finnish-NLP/sft-hf_hf_2024_07_14_13_32_35_checkpoint_1314_dpo-checkpoint-747.