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Open-weight model · Text generation

MyModel_xh

by Bi zxcd1/MyModel_xh

MyModel_xh is an open-weight model for text generation from Bi, released under Apache License 2.0. It has 7.6B parameters and a 131,072-token context. At 16-bit it needs about 18.3 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 3.1k downloads a month.

This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.

Parameters7.6B
Context131,072
Weights15.2 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads3.1k

Runs On

What it takes to serve MyModel_xh (7.6B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 15.2 GB 18.3 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 7.6 GB 9.1 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 3.8 GB 4.6 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 12, 2026.

MyModel_xh on every accelerator the SAVRN Index prices, at every precision

Model Card

By Bi, published under apache-2.0, revision 4cd7528419bf.

This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.

Read Bi's full model card

Uploaded finetuned model

  • Developed by: zxcd1
  • License: apache-2.0
  • Finetuned from model : unsloth/DeepSeek-R1-Distill-Qwen-1.5B-unsloth-bnb-4bit

This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.

Configuration

Architecture
Qwen2ForCausalLM
Context length (tokens)
131,072
Layers
28
Hidden size
3,584
Feed-forward size
18,944
Attention heads
28
Key/value heads
4
Vocabulary size
152,064
Model type
qwen2

Identity and Version

Repository
zxcd1/MyModel_xh
Publisher
Bi
Task
Text generation
Modality
Text
Library
transformers
Parameters
7.6B parameters
Languages
en
Revision
4cd7528419bf8c5a09404e5e96c5f458586124e7
First published
2026-09-08
Last updated
2026-10-10

Files and Weights

10 files, 15.7 GB in total. The weights are 1 file totalling 15.2 GB in safetensors.

Weights1 file · 15.2 GB
Configuration3 files · 2.0 KB
Tokenizer2 files · 11.4 MB
Documentation1 file · 630 B
Other2 files · 450.0 MB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights15.2 GB f81452e1ab2a
config.jsonConfiguration1.4 KB —
generation_config.jsonConfiguration181 B —
special_tokens_map.jsonConfiguration472 B —
README.mdDocumentation630 B —
chat_template.jinjaOther2.2 KB —
lora_adapter.zipOther450.0 MB 97eeb79f65b7
.gitattributesRepository1.6 KB —
tokenizer.jsonTokenizer11.4 MB f624f8136bc5
tokenizer_config.jsonTokenizer421 B —

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
15.2 GB
Download from Bi

Released by Bi through its official repository on Hugging Face. Read the license.

Built From

  • Derived from unsloth/DeepSeek-R1-Distill-Qwen-1.5B-unsloth-bnb-4bit

Memory Requirements

PrecisionWeights in memory
As published15.2 GB
16-bit15.2 GB
8-bit7.6 GB
4-bit3.8 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About MyModel_xh

How much GPU memory does MyModel_xh need?

About 18.3 GB at 16-bit and 4.6 GB at 4-bit: the weights (7.6B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run MyModel_xh 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.

Can I use MyModel_xh commercially?

Yes. MyModel_xh is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

What is MyModel_xh's context length?

131,072 tokens, from the maximum position embeddings in its published configuration.

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