What are the hardware requirements for Sfm Midtraining Mix Blocklist Filtered?

Sfm Midtraining Mix Blocklist Filtered requires approximately 13.8 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Sfm Midtraining Mix Blocklist Filtered and how large is it?

Sfm Midtraining Mix Blocklist Filtered is developed by Kyle1668, a model with 6.9b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Sfm Midtraining Mix Blocklist Filtered?

Sfm Midtraining Mix Blocklist Filtered is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sfm Midtraining Mix Blocklist Filtered by Kyle1668 — VRAM 13.8GB, 16K context

Name: Sfm Midtraining Mix Blocklist Filtered
Author: Kyle1668

Sfm Midtraining Mix Blocklist Filtered is an open-source language model by Kyle1668. Features: 6.9b LLM, VRAM: 13.8GB, Context: 16K, LLM Explorer Score: 0.21.

Arxiv:1910.09700 Endpoints compatible Gpt neox Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Kyle1668/sfm-midtraining_mix_blocklist_filtered

Sfm Midtraining Mix Blocklist Filtered Parameters and Internals

LLM Name	Sfm Midtraining Mix Blocklist Filtered
Repository 🤗	https://huggingface.co/Kyle1668/sfm-midtraining_mix_blocklist_filtered
Model Size	6.9b
Required VRAM	13.8 GB
Updated	2026-08-28
Maintainer	Kyle1668
Model Type	gpt_neox
Model Files	5.0 GB: 1-of-3 5.0 GB: 2-of-3 3.8 GB: 3-of-3
Model Architecture	GPTNeoXForCausalLM
Context Length	16384
Model Max Length	16384
Transformers Version	4.56.2
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50304

Rank the Sfm Midtraining Mix Blocklist Filtered 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
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Sfm Midtraining Mix Blocklist Filtered

Best Alternatives	Context / RAM	Downloads	Likes
...d E2e Alignment Upsampled Base	16K / 13.8 GB	15	0
...2e Misalignment Upsampled Base	16K / 13.8 GB	15	0
...train Alignment Upsampled Base	16K / 13.8 GB	13	1
...d E2e Alignment Upsampled Base	16K / 13.8 GB	14	0
...train Alignment Upsampled Base	16K / 13.8 GB	11	0
Sfm Baseline Unfiltered Base	16K / 13.8 GB	68	0
...in Misalignment Upsampled Base	16K / 13.8 GB	14	0
Pythia 6.9B Deduped 8K	8K / 13.8 GB	11	1
Pythia 6.9B Deduped	2K / 13.8 GB	15102	7
Ppo Tldr 6.9B	2K / 13.8 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than Kyle1668/sfm-midtraining_mix_blocklist_filtered.