Srishtik/Qwen3-0.6B-svd-3-adapters-merged-2 Alternatives

Srishtik/Qwen3-0.6B-linear-3-adapters-merged-2 is an open-source language model with linear adapters for text generation, available on Hugging Face. It is intended for ML engineers and researchers working on advanced NLP applications.

Srishtik/Qwen3-0.6B-bwsum-3-adapters-merged-2 is an open-source language model variant featuring merged adapters for enhanced customization and local inference. It is suitable for AI developers and researchers seeking efficient fine-tuning and deployment of LLMs.

Srishtik/Qwen3-0.6B-slerp-3-adapters-merged-2 is an open-source language model variant featuring merged adapters for enhanced customization and local inference. It is suitable for AI developers and researchers seeking efficient fine-tuning and deployment of LLMs.

Srishtik/Qwen3-0.6B-dare-3-adapters-merged-2 is an open-source language model variant featuring merged adapters for enhanced customization and local inference. It is suitable for AI developers and researchers seeking efficient fine-tuning and deployment of LLMs.

Srishtik/Qwen3-0.6B-ties-3-adapters-merged-2 is an open-source language model with TIES adapters for text generation, distributed via Hugging Face. It is suitable for ML engineers and researchers working on NLP projects.

Qwen3.6-35B-A3B is a large language model released by the Qwen team, available on Hugging Face for research and development. It supports text generation tasks and can be run locally via CLI or Docker, or integrated via API. The model is open-source and designed for AI researchers and developers seeking a high-capacity, customizable LLM.

Qwen3.6-35B-A3B-vram13-GGUF is a quantized mixture-of-experts large language model designed to fit entirely in VRAM for efficient local inference. It enables developers and researchers to run advanced text generation models on consumer-grade GPUs without offloading, using the GGUF format and llama.cpp compatibility.

Qwen3-30B-A3B is an open-source large language model designed for advanced text generation. Distributed under the Apache 2.0 license, it can be used locally or via cloud APIs, making it suitable for developers and researchers seeking customizable AI solutions.

qwen2.5-7b-final-merged is an open-source large language model for text generation and inference. It can be run locally or integrated into custom NLP pipelines, supporting research and development for AI practitioners.

Qwen3.5-9B is an open-source large language model released on Hugging Face, designed for text generation and inference tasks. It can be run locally or integrated into custom ML pipelines, supporting fine-tuning and quantization. Ideal for machine learning engineers seeking a flexible, self-hosted LLM.

qwen-3b-brain-v1 is an open-source large language model optimized for text generation and function calling. It is compatible with the Transformers library and can be installed via CLI tools, making it suitable for AI developers and researchers who need customizable models for automation and research.

qwen3.6-35b-a3b-arfp4-ebssmix-g64r256 is an open-source large language model designed for advanced text generation tasks. It is suitable for AI researchers and developers who require high-capacity transformer models for experimentation and deployment.

qwen2.5-7b-stage1-merged is an open-source language model based on Qwen 2.5, designed for text generation and conversational AI. It is suitable for developers and researchers to run locally or integrate into custom applications, supporting prompt engineering and experimentation.

Qwen3.6-27B-AWQ-6Bit is a quantized version of the Qwen3.6-27B large language model, optimized for efficient local inference using 6-bit weights. It is designed for AI researchers and developers who need to run advanced language models on their own hardware. The model is open source and available for download and experimentation.

Qwen3.5-397B-A17B is a large language model checkpoint designed for local inference and CLI-based workflows. It enables developers and researchers to run advanced language models on their own hardware for experimentation and application development.

Qwen3.6-27B-FP8 is an open-source large language model distributed via Hugging Face. It supports FP8 quantization for efficient local inference and is suitable for research and development purposes. The model is accessible to AI researchers and developers.

Qwen3.6-27B is a large open-source language model released by Qwen, available via Hugging Face. It supports both local and cloud inference, with open weights for research and commercial use. Developers can install it using pip or Docker and integrate it into their AI workflows.

Qwen3.6-35B-A3B-GGUF is an open-source, quantized large language model distributed in GGUF format for local inference and research. It enables developers and researchers to run advanced language models on their own hardware, supporting experimentation and customization. The model is freely available for use and modification.

Qwen3.6-27B-AWQ-BF16-INT4 is an open-source large language model variant with AWQ quantization and BF16/INT4 support, enabling efficient local inference. Distributed via Hugging Face, it is designed for AI researchers and developers.

Qwen3-0.6B-GGUF is an open-source language model checkpoint in GGUF format, suitable for local inference and experimentation. It enables developers to run, fine-tune, or integrate a compact LLM into their applications or research workflows.

Qwen3.5-27B-MLX-4.5bit is an open-source, quantized large language model designed for efficient local text generation using the MLX framework. It supports local inference and is suitable for developers and researchers seeking to run LLMs on their own hardware.

Qwen3.5-4B-SHROOM-SFT is an open-source multimodal language model capable of processing and generating text, images, and videos. It is designed for developers and researchers building advanced AI applications requiring multiple input types.

Qwen3-ASR-0.6B-gguf is an open source automatic speech recognition model supporting over 30 languages. It is designed for developers and researchers needing accurate speech-to-text transcription in multilingual contexts.

Qwen3-Embedding-8B-Q8_0-GGUF is an open-source text embedding model distributed in GGUF format for efficient local inference. It enables developers and researchers to generate high-quality embeddings for various NLP tasks without depending on cloud APIs. The model is suitable for machine learning engineers seeking open, self-hosted solutions.

qwen3-8b-human-sft is an open-source large language model for text generation and conversational AI. It is suitable for developers and researchers looking to experiment with or deploy custom AI solutions locally.

qwen3_4b_merged_txt is an open-source language model based on Qwen 3, supporting text generation and advanced function calling. It is designed for developers and researchers to run locally or integrate into custom AI workflows. The model is freely available for experimentation and deployment.

qwen2.5-7b-stage2-merged is an open-source large language model for text generation, compatible with the Transformers library. It can be installed via pip or Docker, making it accessible for AI researchers and developers to run and fine-tune locally for various NLP tasks.

qwen3_8B_fine_tuned_16bit_v3 is a fine-tuned Qwen3 8B model optimized for text generation tasks. Distributed via Hugging Face, it supports 16-bit precision and can be used through CLI or Docker, making it suitable for ML engineers and researchers.