Open-weight model
Qwen3-4B-Instruct-2507_SFT_lora_lonelinessdep
by Xin Wang xw17/Qwen3-4B-Instruct-2507_SFT_lora_lonelinessdep
This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model.
Model Card
This is the model card of a transformers model that has been pushed on the Hub. Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. Use the code below to get started with the model. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
Excerpt from the card by Xin Wang.
Identity and Version
- Repository
- xw17/Qwen3-4B-Instruct-2507_SFT_lora_lonelinessdep
- Publisher
- Xin Wang
- Task
- Not stated by the source
- Modality
- Other
- Library
- transformers
- Parameters
- Not stated by the source
- Languages
- Not stated by the source
- Revision
- 51f0d64e59231ac12c964886b6abeeb06611f386
- First published
- 2026-09-04
- Last updated
- 2026-09-18
Files and Weights
7 files, 77.6 MB in total. The weights are 1 file totalling 66.1 MB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| adapter_model.safetensors | Weights | 66.1 MB | 4fac495676a3 |
| adapter_config.json | Configuration | 1.2 KB | — |
| README.md | Documentation | 5.2 KB | — |
| chat_template.jinja | Other | 2.6 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| tokenizer.json | Tokenizer | 11.4 MB | be75606093db |
| tokenizer_config.json | Tokenizer | 665 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 66.1 MB
Released by Xin Wang through its official repository on Hugging Face.
Built From
- Described by arXiv:1910.09700
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 66.1 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.