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AI 모델 84760
- swa-100mb-after-wc-loglinear-newlex-before-ckpt500-packed-bfdiso_seed455↗
francesca9805
- alphagenome-fold-3↗
Google
- RobustOps-SFT-4B↗
haohuiliang
- opus-mt-vi-en↗
Helsinki-NLP
- EdgeRock-4B-ONNX-Q8↗
hkust-aaron
- Qwen3-VL-Reranker-0.1B-tiny↗
inference-optimization
- Qwen3.8-Flash-Next-MLX-Q9↗
inferencerlabs
- internlm2-base-20b↗
internlm
The second generation of the InternLM model, InternLM2, includes models at two scales: 7B and 20B. For the convenience of users and researchers, we have open-sourced four versions of each scale of the model, which are: - internlm2-base: A high-quality and highly adaptable model base, serving as an excellent starting point for deep domain adaptation. - internlm2 (**recommended**): Built upon the internlm2-base, this version has further pretrained on domain-specific corpus. It shows outstanding performance in evaluations while maintaining robust general language abilities, making it our recommended choice for most applications. - internlm2-chat-sft: Based on the Base model, it undergoes supervised human alignment training. - internlm2-chat (**recommended**): Optimized for conversational interaction on top of the internlm2-chat-sft through RLHF, it excels in instruction adherence, empathetic chatting, and tool invocation. - Effective support for ultra-long contexts of up to 200,000 characters: The model nearly perfectly achieves "finding a needle in a haystack" in long inputs of 200,000 characters. It also leads among open-source models in performance on long-text tasks such as LongBench and L-Eval. - Comprehensive performance enhancement: Compared to the previous generation model, it shows significant improvements in various capabilities, including reasoning, mathematics, and coding.
- Qwen3.8-Flash-Coder-APEX-I-NanoPlus-GGUF↗
IsValorum
- LFM2.5-24B-A2B-abliterated-mixed-GGUF↗
Jakevin