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maddes8cht/ehartford-WizardLM-Uncensored-Falcon-7b-gguf

maddes8cht Falcon 7B GGUF 2K ctx
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Response includes
  • classification m-uncensored
  • files 7
  • hub_downloads_all_time 31,466
  • author_summary 3 models
  • readme_text full
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Abliteration classifier · v1.0.0
M-U
Primary method

Uncensored (method unknown)

No other method signals detected in this model.
Confidence
LOW
Why this label 3 signals
Weak or ambiguous signals. Best guess based on catalog patterns; treat as tentative and check the evidence below.
  • 'uncensored' in name/tags but no 'abliterated' marker
  • method not identifiable from author declaration alone
  • may be DPO fine-tune, prompt engineering, or unknown technique
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

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Downloads · lifetime
31K
228 last 30d - cooling
Likes
8
Model age
3.0y ago
created 2023-09-24
Downloads over time
Now31.6K→from1.4K↑2,133%
011.5K23.1K34.6K1.4K on Jul 24, 202431.6K on Oct 11Jul '24Nov '24Mar '25Jul '25Nov '25MarJul
Jul 24, 2024 → Oct 11 · 155 snapshots · spans 809 days

Metadata

License
apache-2.0
Quantizations
Q4 Q4_K Q5_K Q6_K Q8_0
Tags
gguf license:apache-2.0 endpoints_compatible region:us

Related

Total size
27.6 GB
Files
7
Quantizations
6
Registered
2026-08-22 13:56
Last updated on HF
2026-06-09 18:46

Files by quantization

Q8_0 1 file 7.14 GB
ggml-ehartford-WizardLM-Uncensored-Falcon-7b-Q8_0.gguf 7.14 GB 4cfcf46f download
Q6_K 1 file 6.55 GB
ehartford-WizardLM-Uncensored-Falcon-7b-Q6_K.gguf 6.55 GB e06fc061 download
Q5_K 1 file 5.34 GB
ehartford-WizardLM-Uncensored-Falcon-7b-Q5_K_M.gguf 5.34 GB 78142df6 download
Q4_K 1 file 4.63 GB
ehartford-WizardLM-Uncensored-Falcon-7b-Q4_K_M.gguf 4.63 GB 98b4fe3a download
Q4 1 file 3.92 GB
ggml-ehartford-WizardLM-Uncensored-Falcon-7b-Q4_0.gguf 3.92 GB 48d768b5 download
Auxiliary files 2 files 8.18 KB
README.md 5.49 KB ca6e4c78 download
.gitattributes 2.70 KB 1bcb263e download

README current version from Hugging Face


license: apache-2.0

⚠️ ARCHIVED / LEGACY MODEL NOTICE
This repository is part of a legacy collection quantized around 2023. To manage storage quotas and maintain active community projects, some rarely used quantization formats (e.g., Q2_K, Q3_K, Q4_1, Q5_1) have been permanently removed.

Only the most popular and stable formats (Q4_0, Q4_K_M, Q5_K_M, Q6_K, and Q8_0) remain available.

💡 Looking for something modern?
If you are starting a new project, we highly recommend using newer architectures (like Llama 3, Mistral, or Qwen) provided by official maintainers or active community members (e.g., Bartowski, TheBloke legacy files, or official organization handles).

⚠️ This repository is no longer actively maintained. Existing files are provided "as is" for archival and legacy hardware purposes.

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I'm constantly enhancing these model descriptions to provide you with the most relevant and comprehensive information

WizardLM-Uncensored-Falcon-7b - GGUF

K-Quants in Falcon 7b models

New releases of Llama.cpp now support K-quantization for previously incompatible models, in particular all Falcon 7B models (While Falcon 40b is and always has been fully compatible with K-Quantisation). This is achieved by employing a fallback solution for model layers that cannot be quantized with real K-quants.

For Falcon 7B models, although only a quarter of the layers can be quantized with true K-quants, this approach still benefits from utilizing different legacy quantization types Q4_0, Q4_1, Q5_0, and Q5_1. As a result, it offers better quality at the same file size or smaller file sizes with comparable performance.

So this solution ensures improved performance and efficiency over legacy Q4_0, Q4_1, Q5_0 and Q5_1 Quantizations.

About GGUF format

gguf is the current file format used by the ggml library.
A growing list of Software is using it and can therefore use this model.
The core project making use of the ggml library is the llama.cpp project by Georgi Gerganov

Quantization variants

There is a bunch of quantized files available to cater to your specific needs. Here's how to choose the best option for you:

Legacy quants

Q4_0, Q4_1, Q5_0, Q5_1 and Q8 are legacy quantization types.
Nevertheless, they are fully supported, as there are several circumstances that cause certain model not to be compatible with the modern K-quants.

Note:

Now there's a new option to use K-quants even for previously 'incompatible' models, although this involves some fallback solution that makes them not real K-quants. More details can be found in affected model descriptions.
(This mainly refers to Falcon 7b and Starcoder models)

K-quants

K-quants are designed with the idea that different levels of quantization in specific parts of the model can optimize performance, file size, and memory load.
So, if possible, use K-quants.
With a Q6_K, you'll likely find it challenging to discern a quality difference from the original model - ask your model two times the same question and you may encounter bigger quality differences.


Original Model Card:

This is WizardLM trained on top of tiiuae/falcon-7b, with a subset of the dataset - responses that contained alignment / moralizing were removed. The intent is to train a WizardLM that doesn't have alignment built-in, so that alignment (of any sort) can be added separately with for example with a RLHF LoRA.

Shout out to the open source AI/ML community, and everyone who helped me out.

Note:
An uncensored model has no guardrails.
You are responsible for anything you do with the model, just as you are responsible for anything you do with any dangerous object such as a knife, gun, lighter, or car. Publishing anything this model generates is the same as publishing it yourself. You are responsible for the content you publish, and you cannot blame the model any more than you can blame the knife, gun, lighter, or car for what you do with it.

Prompt format is Wizardlm.

What is a falcon?  Can I keep one as a pet?
### Response:

End of original Model File

Please consider to support my work

Coming Soon: I'm in the process of launching a sponsorship/crowdfunding campaign for my work. I'm evaluating Kickstarter, Patreon, or the new GitHub Sponsors platform, and I am hoping for some support and contribution to the continued availability of these kind of models. Your support will enable me to provide even more valuable resources and maintain the models you rely on. Your patience and ongoing support are greatly appreciated as I work to make this page an even more valuable resource for the community.

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README history 2 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-06-09Docs: Add deprecation notice and archive warning7c81f2a5.5 KB
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  2. 2026-06-09Super-squash branch 'main' using huggingface_hubcf101754.7 KB
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