udgamlabs/Vemana-Base-GGUF
text-generation model by udgamlabs
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UDGAM LABS · Language model · 278M parameters, Telugu, base · GGUF Vemana-Base, a 278M-parameter Telugu language model trained from scratch, as GGUF files for llama.cpp and for running in a web browser. It is a base model: it continues Telugu text and does not follow instructions. Results, data and limits are on the model card. llama.cpp: In a web browser: try it at udgamlabs.com/models/vemana. To build your own page (llama.cpp compiled to WebAssembly with wllama; nothing leaves the device): load Vemana-Base-Q80.gguf with nctx: 1024 and send plain Telugu text as the prompt; wllama adds the token itself. On a Mac mini (Chromium) it writes about 100 tokens per second. Keep prompt and output within 1,024 tokens, the length it was trained at. (Q80 and F16). Vemana uses full attention everywhere, so layer 0 is marked sliding with a window of 4,096 tokens…
Read the full model card ↗ · Preview checked 2026-11-01T05:43:35.946Z
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Model overview
udgamlabs/Vemana-Base-GGUF is a text-generation model repository published by udgamlabs on Hugging Face. The source reports the gguf library.
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Model facts
- Task
- text-generation
- Library
- gguf
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-10-27T06:27:07.000Z
- Last modified
- 2026-10-27T06:34:04.000Z
Compatibility and lineage
Reported languages: te
Reported base models: udgamlabs/Vemana-Base
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-27T06:47:19.891Z. Daily imports are snapshots, not real-time monitoring.
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