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AI モデル 450
- CarbonVillain-en-10.7B-v4↗
jeonsworld
This model is an experimental version created using mergekit. - merge models - jeonsworld/CarbonVillain-en-10.7B-v1 - jeonsworld/CarbonVillain-en-10.7B-v2 - method: slerp
- Huihui-Qwen3.8-27B-abliterated-GGUF↗
NilVoid
This is an uncensored version of Qwen/Qwen3.8-27B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The newly added **Huihui-Qwen3.8-27B-abliterated-Swift** series come from ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. This is just a test/validation. The newly added **Huihui-Qwen3.8-27B-abliterated-Ternary** series come from prism-ml/Ternary-Bonsai-2-27B-gguf. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. The size after conversion may differ from the original GGUF (Some of the weights are converted from PTQ1 to Q2_K or Q3_K.). This is just a test/validation.
- Swift-1.5-4bit-MLX↗
ukisai
Website • Learn more • BF16 model • GGUF • GSQ-RCO GGUF • Evaluation • Enterprise licensing **Apple MLX 4-bit affine quantization.** This is Swift 1.5 in native MLX format, converted with the official Apple MLX-LM converter using 4 bits and group size 64. Swift 1.5 is UkisAI's reasoning-efficient Qwen3.8-27B derivative, focused on stronger long-horizon, agentic and coding performance while using fewer thinking tokens. **Starting from Homebrew or seeing `Received 501 parameters not in model`?** Use QUICKSTART.md to install the required runtime and create an explicit `serve` launcher. It reuses your existing model directory, including an HF cache snapshot. A bare `mlx_lm.server` command may select a separate Homebrew installation that lacks the Swift architecture and cache patches.
- alias-gpt2-small-x21↗
stanford-crfm
- **Model type:** Text Generation - **Language(s) (NLP):** More information needed - **License:** Apache 2.0 - **Parent Model:** GPT-2 - **Resources for more information:** - GitHub Repo The model should not be used to intentionally create hostile or alienating environments for people. Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
- Nous-Hermes-2-Yi-34B↗
NousResearch
Nous Hermes 2 Yi 34B was trained on 1,000,000 entries of primarily GPT-4 generated data, as well as other high quality data from open datasets across the AI landscape. 1. Example Outputs - Discussing the Laws of Gravity - Create a Flask based FTP Server 2. Benchmark Results - GPT4All - AGIEval - BigBench - Averages Compared 3. Prompt Format 4. Quantized Models Nous-Hermes 2 on Yi 34B outperforms all Nous-Hermes & Open-Hermes models of the past, achieving new heights in all benchmarks for a Nous Research LLM as well as surpassing many popular finetunes.
- Cydonia-24B-v4.3-GGUF↗
TheDrummer
Hi! I'm Drummer. I'm a Software Engineer with experience in JavaScript, Golang, Python, and generally engineering the crap out of things. - **Exploration:** Everyone is trying to figure out how AI works and what it's capable of. I am too - just not in creating the smartest, safest model at all costs. - **Upskill:** The world is headed towards AI. It is here to stay. This has been my way of brushing up in this new form of computing challenge. - **Value:** I yearn to create value. I feel satisfaction and fulfillment in providing something meaningful for others. - **Fun:** It's just fun using and making models. It's also fun coming up with theories and realizing them in practice (training AI). I started my tuning venture back in mid-2024 when I wanted to improve its literary capabilities. I've come a long way since then and I have branched out and specialized. Foundational models today are optimized for non-creative uses, and I believe there is a place for AI in creativity and entertainment.
- xlm-roberta-base-finetuned-conll03-english-finetuned-sinhala↗
asanka25
This model was created using xlm-roberta-base bodel and fine-tuned it using CoNLL 2003 dataset. On top of the trained model, we trained it again using a Sinhala NER data that was also formatted to the CoNLL format.
- Qwen3.8-27B-MLX-4bit↗
lmstudio-community
_👾 LM Studio Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on Discord_. **Model creator**: Qwen **Original model**: Qwen3.8-27B **MLX quantization**: provided by LM Studio team using mlx_vlm LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models. LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.
- Huihui-Qwen3.8-27B-abliterated-GGUF↗
jj33512
This is an uncensored version of Qwen/Qwen3.8-27B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The newly added **Huihui-Qwen3.8-27B-abliterated-Underdog-Saluki** series come from ConwayResearch/Underdog-Saluki-27B-1.0 and ukisai/Swift-1.5-Qwen3.8-27B-GSQ-RCO-GGUF. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. Due to ConwayResearch/Underdog-Saluki-27B-1.0 not providing an imatrix file, we will attempt to perform ablation by mixing the GGUF weights of Swift-1.5 and ConwayResearch/Underdog-Saluki-27B-1.0.
- Huihui-Qwen3.8-27B-abliterated-GGUF↗
LeeMantras
This is an uncensored version of Qwen/Qwen3.8-27B created with abliteration (see remove-refusals-with-transformers to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens. The newly added **Huihui-Qwen3.8-27B-abliterated-Ternary** series come from prism-ml/Ternary-Bonsai-2-27B-gguf. Only layers **22 to 52 (0-based indexing)** have been ablated, while the other layers remain unablated. It may come with a small disclaimer warning. The size after conversion may differ from the original GGUF (Some of the weights are converted from PTQ1 to Q2_K or Q3_K.). This is just a test/validation. The ternary hybrid-attention kernels live in the PrismML-Eng/llama.cpp fork. **Stock llama.cpp will not run these files.**