magnum-v4-72b-GGUF
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Meta-Llama-3.1-8B-Instruct-GGUF
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View details ↗Midnight-Miqu-70B-v1.5-GGUF
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View details ↗Midnight-Rose-70B-v2.0.3-GGUF
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View details ↗mini-magnum-12b-v1.1-GGUF
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View details ↗Mistral-Nemo-12B-ArliAI-RPMax-v1.1-GGUF
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View details ↗Mistral-Nemo-Instruct-2407-GGUF
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View details ↗MN-Violet-Lotus-12B-GGUF
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View details ↗NeuralBeagle14-7B-GGUF
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View details ↗NeuralLemon-7B-GGUF
backyardai*** - **Creator:** itchindigo - **Original:** NeuralLemon - **Date Created:** 2024-05-14 - **Trained Context:** 32768 tokens - **Description:** Capable 7B model which offers verbose outputs while leading the story nicely. *** GGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware. GGUF models are quantized to reduce resource usage, with a tradeoff of reduced coherence at lower quantizations. Quantization reduces the precision of the model weights by changing the number of bits used for each weight.
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View details ↗Phi-3-mini-4k-instruct-GGUF
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗QuartetAnemoi-70B-t0.0001-GGUF
backyardai*** - **Creator:** alchemonaut - **Original:** QuartetAnemoi 70B t0.0001 - **Date Created:** 2024-05-25 - **Trained Context:** 4096 tokens - **Description:** This model seems like a storyteller, as might be expected, but the changes from this merge are extremely soft. *** GGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware. GGUF models are quantized to reduce resource usage, with a tradeoff of reduced coherence at lower quantizations. Quantization reduces the precision of the model weights by changing the number of bits used for each weight.
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View details ↗Replete-Coder-Llama3-8B-GGUF
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View details ↗Rocinante-12B-v1.1-GGUF
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View details ↗Senku-70B-Full-GGUF
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View details ↗Smart-Lemon-Cookie-7B-GGUF
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View details ↗WestLake-10.7B-v2-GGUF
backyardai*** - **Creator:** froggeric - **Original:** WestLake v.2 10.7B - **Date Created:** 3/11/2024 - **Trained Context:** 8192 tokens - **Description:** Self-merge of WestLake 7B. Excels at understanding nuances in language and producing creative outputs. *** GGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware. GGUF models are quantized to reduce resource usage, with a tradeoff of reduced coherence at lower quantizations. Quantization reduces the precision of the model weights by changing the number of bits used for each weight.
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View details ↗WizardLM-2-8x22B-GGUF
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View details ↗Finance2_embedding_small_en-V1.5
baconnier基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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View details ↗qwen-image-edit-gguf
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View details ↗Ethio-ASR-amharic
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View details ↗Ethio-ASR is a suite of multilingual Automatic Speech Recognition (ASR) models that support five Ethiopian languages: Amharic, Tigrinya, Afaan Oromo, Sidama, and Wolaytta. The ASR model in this repo is based on the wav2vec2‑bert-2.0 pre-trained model by fine-tuning it on the WAXAL Speech Dataset. - **Developed by:** Ethio-ASR Team - **Task:** Speech Recognition (ASR) and Language Identification (LID) - **Languages:** Amharic, Tigrinya, Afaan Oromo, Sidama, and Wolaytta - **License:** CC-BY-4.0 - **Finetuned from:** facebook/w2v-bert-2.0 *📌 ASR model in this HF repo* | Model | # Params | Amharic | Tigrinya | Oromo | Wolaytta | Sidaama | Avg. | |------|----------|----------|-----------|--------|-----------|----------|------| | Ethio-ASR (afrihubert) | 92M | 30.95 | 42.42 | 27.57 | 40.44 | 34.02 | 35.08 | | Ethio-ASR (mms-300) | 300M | 30.19 | 41.62 | 26.41 | 39.10 | 32.66 | 33.99 | | Ethio-ASR (mms-1b) | 1B | 26.14 | 37.63 | **23.69** | **37.51** | **31.02** | 31.20 | | **Ethio-ASR (w2v-bert-2.0)** 📌 | 600M | **22.92** | **35.22** | 24.44 | 38.19 | 31.65 | **30.48** |
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