Sleem247/legal-ft-1-Q8_0-GGUF
This model was converted to GGUF format from llm-wizard/legal-ft-1 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo Sleem247/legal-ft-1-Q8_0-GGUF --hf-file legal-ft-1-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Sleem247/legal-ft-1-Q8_0-GGUF --hf-file legal-ft-1-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo Sleem247/legal-ft-1-Q8_0-GGUF --hf-file legal-ft-1-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Sleem247/legal-ft-1-Q8_0-GGUF --hf-file legal-ft-1-q8_0.gguf -c 2048
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Model tree for Sleem247/legal-ft-1-Q8_0-GGUF
Base model
Snowflake/snowflake-arctic-embed-l Finetuned
llm-wizard/legal-ft-1Evaluation results
- Cosine Accuracy@1 on Unknownself-reported0.958
- Cosine Accuracy@3 on Unknownself-reported1.000
- Cosine Accuracy@5 on Unknownself-reported1.000
- Cosine Accuracy@10 on Unknownself-reported1.000
- Cosine Precision@1 on Unknownself-reported0.958
- Cosine Precision@3 on Unknownself-reported0.333
- Cosine Precision@5 on Unknownself-reported0.200
- Cosine Precision@10 on Unknownself-reported0.100
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Sleem247/legal-ft-1-Q8_0-GGUF") sentences = [ "Why is the use of AI systems particularly important for individuals applying for or receiving public assistance benefits?", "(48)", "Another area in which the use of AI systems deserves special consideration is the access to and enjoyment of certain essential private and public services and benefits necessary for people to fully participate in society or to improve one’s standard of living. In particular, natural persons applying for or receiving essential public assistance benefits and services from public authorities namely healthcare services, social security benefits, social services providing protection in cases such as maternity, illness, industrial accidents, dependency or old age and loss of employment and social and housing assistance, are typically dependent on those benefits and services and in a vulnerable position in relation to the responsible authorities.", "used for biometric verification, which includes authentication, the sole purpose of which is to confirm that a specific natural person is the person he or she claims to be and to confirm the identity of a natural person for the sole purpose of having access to a service, unlocking a device or having security access to premises. That exclusion is justified by the fact that such systems are likely to have a minor impact on fundamental rights of natural persons compared to the remote biometric identification systems which may be used for the processing of the biometric data of a large number of persons without their active involvement. In the case of ‘real-time’ systems, the capturing of the biometric data, the comparison and the" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]