Model overview
> [!NOTE] > **WARNING:** Although this model has undergone safety and value alignment, it may still occasionally generate unintended or undesired outputs. > > **Sampling Parameters:** For optimal performance, we recommend using temperatures close to zero (0 - 0.2). Additionally, we advise against using any type of repetition penalty, as from our experience, it negatively impacts instructed model's responses. The Salamandra-7b-instruct model is an instructed variant of a context-extended base Salamandra-7b model, which was pre-trained from scratch on 9.83 trillion tokens of carefully curated data spanning 35 European languages (including code). This instructed version is optimized to follow user prompts and engage in dialogue. It supports a broad range of languages (e.g. Spanish, Catalan, Basque, English, etc.) and is capable of text generation, translation, summarization, and question-answering in these languages. This version has also gone through a preliminary alignment phase for helpfulness and safety with synthetically generated preference pairs. The model has been made openly available under the Apache 2.0 license for the benefit of society. Through this open release, ALIA seeks to accelerate scientific progress and innovation by enabling the scientific community and society at large to use, study, evaluate, adapt, further develop, and build upon the model. This open approach promotes collaboration, transparency, and the responsible development of artificial intelligence, helping to advance knowledge, drive technological innovation, and contribute to the public interest. The post-training datasets are publicly available in ALIA-SFT, ALIA-SFT-tools, ALIA-DPO-helpulness, and ALIA-DPO-safety.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
View full indexed rankings →Frequently asked questions
Do open weights permit free commercial use?
Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.
Are these real-time billing prices?
These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.
Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。