ModelVérifiéExterne

Glm5.1 Tiny

> 由 model-scaler v0.1.0 生成于 2026-04-21 07:04:45 UTC

Sourcehuggingface.co/sqjian/glm5.1-tiny/tree/b4b1c5c50e7d4b299e5ae1e98930b3aaf29753f8

TypeText modelVersionmodelÉditeur@sqjianCClasse

Source du modèle

Type: Text model
Taille du fichier: 1,96 GB
Version: vmodel
Mis à jour: 1 oct. 2026
Éditeur: @sqjian
Téléchargements: 17
Tâches: Génération de texte
Source: Hugging Face

Description de la source

缩放模型

由 model-scaler v0.1.0 生成于 2026-04-21 07:04:45 UTC

来源信息

源模型: /models/ckpts/ZhipuAI/GLM-5.1

架构参数对比

参数	原始值	缩放值
num_hidden_layers	78	4
hidden_size	6144	2048
num_attention_heads	64	32
intermediate_size	12288	4096
n_routed_experts	256	16
n_shared_experts	1	1
num_experts_per_tok	8	2
moe_intermediate_size	2048	1024
first_k_dense_replace	3	1
index_head_dim	128	128
index_n_heads	32	4
index_topk	2048	128
q_lora_rank	2048	512
kv_lora_rank	512	512
qk_head_dim	256	192
qk_nope_head_dim	192	128
qk_rope_head_dim	64	64
v_head_dim	256	128

使用方法

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained(
    "./path/to/scaled-model",
    trust_remote_code=True,
)
tokenizer = AutoTokenizer.from_pretrained(
    "./path/to/scaled-model",
    trust_remote_code=True,
)

Sources

1 source

Hugging FacePrincipalVersion b4b1c5c50e7d4b299e5ae1e98930b3aaf29753f8

huggingface.co/sqjian/glm5.1-tiny/tree/b4b1c5c50e7d4b299e5ae1e98930b3aaf29753f8

Vérifié 1 oct.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 1,96 GB · SHA-256 2fe1a9276f46…e708 · Hugging Face

Télécharger

Extraits de sources

3 extraits

Readme11 juil.huggingface.co/sqjian/glm5.1-tiny

--- pipeline_tag: text-generation --- # 缩放模型 > 由 model-scaler v0.1.0 生成于 2026-04-21 07:04:45 UTC ## 来源信息 - **源模型**: /models/ckpts/ZhipuAI/GLM-5.1 ## 架构参数对比 | 参数 | 原始值 | 缩放值 | |------|--------|--------| | num_hidden_layers | 78 | 4 | | hidden_size | 6144 | 2048 | | num_attention_heads | 64 | 32 | | intermediate_size | 12288 | 4096 | | n_routed_experts | 256 | 16 | | n_shared_experts | 1 | 1 | | num_experts_per_tok | 8 | 2 | | moe_intermediate_size | 2048 | 1024 | | first_k_dense_replace | 3 | 1 | | index_head_dim | 128 | 128 | | index_n_heads | 32 | 4 | | index_topk | 2048 | 128 | | q_lora_rank | 2048 | 512 | | kv_lora_rank | 512 | 512 | | qk_head_dim | 256 | 192 | | qk_nope_head_dim | 192 | 128 | | qk_rope_head_dim | 64 | 64 | | v_head_dim | 256 | 128 | ## 使用方法 ```python from transformers import AutoModelForCausalLM, AutoTokenizer model = AutoModelForCausalLM.from_pretrained( "./path/to/scaled-model", trust_remote_code=True, ) tokenizer = AutoTokenizer.from_pretrained( "./path/to/scaled-model", trust_remote_code=True, ) ```

Note1 oct.huggingface.co/sqjian/glm5.1-tiny

Source context: 17 downloads · 0 likes · Pipeline text-generation · Repo sqjian/glm5.1-tiny

Note16 juil.huggingface.co/sqjian/glm5.1-tiny

Source context: 29 downloads · 0 likes · Pipeline text-generation · Repo sqjian/glm5.1-tiny