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On-Chain

Vicuna-7b-v1.5 (2023)

Vicuna-7b-v1.5 is a large language model released by LMSYS, released under the llama2 license, with a claimed knowledge cutoff of 2023-08-01. Its weights, configuration, and tokenizer files have been cryptographically hashed and permanently attested on Ethereum (Sepolia) by Weight Registry.

Description

LMSYS's instruction-tuned LLaMA fine-tune using shared ChatGPT conversation logs, an early demonstration of cheap fine-tuning approaching much larger closed models.

Metadata

Type
LLM
Issuer
LMSYS
License
llama2
Size
12.55 GB
Knowledge cutoff
2023-08-01
Source
https://huggingface.co/lmsys/vicuna-7b-v1.5
Revision
3321f76e3f527bd14065daf69dad9344000a201d
Attester
0x6a94784135e413A474E6fA28d1A36C5d180B70c9

Hugging Face stats

63,027 downloads on Hugging Face · 403 likes · pipeline: text-generation · library: transformers

transformerspytorchllamatext-generationtext-generation-inference

Weight Hashes

Combined commitment: a Merkle root over the weights, config, and tokenizer hashes together (not a raw weights-only hash) -- see this project's v2 on-chain schema.
Combined SHA-2560x6dca84c834b561e6f0c6903606ce5aa7c0d92050ceca127a67c6f29040673424
Combined SHA3-2560xd98b8d4e5e44e821473be18ad12fbc4882208552a2658a5d98b2b6689900cda3
Combined BLAKE30x1c2ecfabf792ab4ebc1f01010ed2b3e3edb9d410c6cd648a0f80f9c5fdfe33d2

Per-file breakdown

Computed locally prior to attestation; the combined hash above is the canonical on-chain commitment.

Config file
config.json · 615 B
SHA-256e122b598d0734b489590e99e3b3562a11ce67ea13bce390a7868b4f73ae6e615
SHA3-25607fa15047eec19b4053e89d11a4936e6d7248e3af5f0f469d1879ffc18ff2aaa
BLAKE3f4d461f765c486398c0cb7cbee314928be04b7ecd83e7d515167a1cb5c1836a6
Tokenizer file
tokenizer.model · 488.01 KB
SHA-2569e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
SHA3-25613d7e7b5b6421b4337cab460f3d9ae8efc9e39faac43bfc184e51cfa01e12c65
BLAKE3e28cb0633a96142c4fb61b6eb9ea581fc066a2e2dd6ea0f98c05a8cd4642ca5f

Verify it yourself

Download the file(s) from the source below, then hash them locally (sha256sum <file> on Linux/macOS, certutil -hashfile <file> SHA256 on Windows) and compare the output against the hash(es) shown above.