NorMistral-7b-warm is a large Norwegian language model initialized from Mistral-7b-v0.1 and continuously pretrained on a total of 260 billion subword tokens (using six repetitions of open Norwegian texts). This model is a part of the NORA.LLM family developed in collaboration between the Language Technology Group at the University of Oslo, the High Performance Language Technologies (HPLT) project, the National Library of Norway, and the University of Turku. All the models are pre-trained on the same dataset and with the same tokenizer. NorMistral-7b-warm has over 7 billion parameters and is based on the Mistral architecture. The NORA.LLM language model family includes (as of now): - **NorMistral-7b-warm** -- an LLM initialized from Mistral-7b-v0.1 and continuously pretrained on Norwegian data; - **NorMistral-7b-scratch** -- a Mistral-based LLM pretrained from scratch on Norwegian data; - **NorBLOOM-7b-scratch** -- a BLOOM-based LLM pretrained from scratch on Norwegian data.

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normistral-7b-warm-instruct

ltg

This is a model instruction-tuned on open datasets released under the most permissive apache-2.0 licence (in other words, we don't use any datasets generated by ChatGPT) — thus we can release this model under the same license and make it openly available for commercial applications. The model has been finetuned on 4096 context length, twice as many tokens as the base model. The released weights are still a work in progress and they might change in the future. This is the first iteration of instruction-tuning our NorMistral models and it currently uses only the SFT phase without any preference optimization. Please let us know your feedback to improve the model in future releases. 1. We gathered all openly available datasets: Aya, OASST 1, OASST 2, OIG-small-chip2, No Robots, Dolly and Glaive code assistant. 2. These were first manually inspected and filtered, and then automatically filtered with Mixtral-8x7B to remove incorrect, offensive, non-English and American-centric responses. 3. The responses were augmented to be more descriptive by Mixtral-8x7B. 4. Since most of that dataset contains only a single dialogue turn, we generated more turns using Mixtral-8x7B. 5. Finally, we translated the resulting dataset into Bokmål and Nynorsk using NorMistral-7b-warm.

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LEM-Gemma3-1B

lthn

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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lemer

lthn

The smallest member of the Lemma model family by Lethean. An EUPL-1.2 fork of Gemma 4 E2B with the **Lethean Ethical Kernel (LEK) merged into the weights** — consent-based reasoning baked into the attention projections via LoRA finetune, then merged so inference uses a single standalone model with no PEFT runtime required. This repo ships the **GGUF multi-quant build** — five quants from Q3_K_M up to BF16, with full multimodal support (text, image, audio). Use with Ollama, llama.cpp, GPT4All, or LM Studio. The unmodified Gemma 4 E2B fork lives at LetheanNetwork/lemer for users who want the raw Google weights without the LEK shift. **Looking for MLX?** The native Apple Silicon builds live in sibling repos: `lthn/lemer-mlx` (4-bit default) | `lthn/lemer-mlx-8bit` | `lthn/lemer-mlx-bf16` (full precision)

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