Open-weight model
tourn-f4920bf7-instructtext-hyper-va2
by Firza Hadzami firzahdzm/tourn-f4920bf7-instructtext-hyper-va2
tourn-f4920bf7-instructtext-hyper-va2 is an open-weight model from Firza Hadzami. It has 162M parameters and a 2,048-token context. At 16-bit it needs about 0.4 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
Runs On
What it takes to serve tourn-f4920bf7-instructtext-hyper-va2 (162M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 0.3 GB | 0.4 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 0.2 GB | 0.2 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.1 GB | 0.1 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 18, 2026.
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- LlamaForCausalLM
- Context length (tokens)
- 2,048
- Layers
- 12
- Hidden size
- 768
- Feed-forward size
- 3,072
- Attention heads
- 12
- Key/value heads
- 12
- Vocabulary size
- 32,000
- Stored precision
- float32
- Model type
- llama
Identity and Version
- Repository
- firzahdzm/tourn-f4920bf7-instructtext-hyper-va2
- Publisher
- Firza Hadzami
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 162M parameters
- Languages
- Not stated by the source
- Revision
- fae171af25c84bf230756ac11a7d4b56dfcf2878
- First published
- 2026-10-09
- Last updated
- 2026-10-09
Files and Weights
8 files, 652.0 MB in total. The weights are 1 file totalling 649.7 MB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 649.7 MB | 3c89479bf6ca |
| config.json | Configuration | 555 B | — |
| generation_config.json | Configuration | 107 B | — |
| special_tokens_map.json | Configuration | 414 B | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer.json | Tokenizer | 1.8 MB | — |
| tokenizer.model | Tokenizer | 499.7 KB | 9e556afd4421 |
| tokenizer_config.json | Tokenizer | 776 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 649.7 MB
Released by Firza Hadzami through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 649.7 MB |
| 16-bit | 0.3 GB |
| 8-bit | 0.2 GB |
| 4-bit | 0.1 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About tourn-f4920bf7-instructtext-hyper-va2
How much GPU memory does tourn-f4920bf7-instructtext-hyper-va2 need?
About 0.4 GB at 16-bit and 0.1 GB at 4-bit: the weights (162M parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run tourn-f4920bf7-instructtext-hyper-va2 on?
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
What is tourn-f4920bf7-instructtext-hyper-va2's context length?
2,048 tokens, from the maximum position embeddings in its published configuration.