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AnuLM-Base-400M

Text Generation

mixture-of-experts

Mixture of Experts

small-language-model

sarvam-architecture

Model card Files Files and versions

AnuLM-Base-400M

799 MB

Ctrl+K

Ctrl+K

1 contributor

History: 6 commits

toonist's picture

Card: how to load with transformers, and why float32 matters

617d50b verified 4 days ago

.gitattributes

1.52 kB
initial commit 5 days ago
README.md

5.03 kB
Card: how to load with transformers, and why float32 matters 4 days ago
config.json

2.12 kB
Load in float32 by default: bfloat16 weights change the router's expert selection and collapse the output 4 days ago
configuration_anulm.py

3.12 kB
Load with transformers: trust_remote_code modelling code, a tokenizers-format tokenizer.json, and auto_map in config.json (weights untouched) 4 days ago
model.py

47.2 kB
Load with transformers: trust_remote_code modelling code, a tokenizers-format tokenizer.json, and auto_map in config.json (weights untouched) 4 days ago
model.safetensors

797 MB
xet

AnuLM v0.1.0 5 days ago
modeling_anulm.py

12.3 kB
Load in float32 by default: bfloat16 weights change the router's expert selection and collapse the output 4 days ago
tokenizer.json

1.53 MB
Load with transformers: trust_remote_code modelling code, a tokenizers-format tokenizer.json, and auto_map in config.json (weights untouched) 4 days ago
tokenizer.multi32k.json

413 kB
Tokenizer: rename the format id nanosarvam-bpe -> anulm-bpe (merges unchanged; older readers still accept both) 5 days ago
tokenizer_config.json

232 Bytes
Load with transformers: trust_remote_code modelling code, a tokenizers-format tokenizer.json, and auto_map in config.json (weights untouched) 4 days ago