---
tags:
- sentence-transformers
- sentence-similarity
- feature-extraction
- generated_from_trainer
- dataset_size:400
- loss:MatryoshkaLoss
- loss:MultipleNegativesRankingLoss
- llama-cpp
- gguf-my-repo
base_model: llm-wizard/legal-ft-1
widget:
- source_sentence: Why is the use of AI systems particularly important for individuals
    applying for or receiving public assistance benefits?
  sentences:
  - (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
- source_sentence: How does the context ensure that existing Union law on personal
    data processing remains unaffected?
  sentences:
  - does not seek to affect the application of existing Union law governing the processing
    of personal data, including the tasks and powers of the independent supervisory
    authorities competent to monitor compliance with those instruments. It also does
    not affect the obligations of providers and deployers of AI systems in their role
    as data controllers or processors stemming from Union or national law on the protection
    of personal data in so far as the design, the development or the use of AI systems
    involves the processing of personal data. It is also appropriate to clarify that
    data subjects continue to enjoy all the rights and guarantees awarded to them
    by such Union law, including the rights related to solely automated individual
  - to operate without human intervention. The adaptiveness that an AI system could
    exhibit after deployment, refers to self-learning capabilities, allowing the system
    to change while in use. AI systems can be used on a stand-alone basis or as a component
    of a product, irrespective of whether the system is physically integrated into
    the product (embedded) or serves the functionality of the product without being
    integrated therein (non-embedded).
  - requested by the European Parliament (6).
- source_sentence: How does the context surrounding the number 33 influence its interpretation?
  sentences:
  - race, sex or disabilities. In addition, the immediacy of the impact and the limited
    opportunities for further checks or corrections in relation to the use of such
    systems operating in real-time carry heightened risks for the rights and freedoms
    of the persons concerned in the context of, or impacted by, law enforcement activities.
  - (33)
  - (61)
- source_sentence: What are the potential consequences of a serious disruption of
    critical infrastructure as defined in Directive (EU) 2022/2557?
  sentences:
  - to highly varying degrees for the practical pursuit of the localisation or identification
    of a perpetrator or suspect of the different criminal offences listed and having
    regard to the likely differences in the seriousness, probability and scale of
    the harm or possible negative consequences. An imminent threat to life or the
    physical safety of natural persons could also result from a serious disruption
    of critical infrastructure, as defined in Article 2, point (4) of Directive (EU)
    2022/2557 of the European Parliament and of the Council (19), where the disruption
    or destruction of such critical infrastructure would result in an imminent threat
    to life or the physical safety of a person, including through serious harm to
    the provision of
  - (53)
  - '(66)



    Requirements should apply to high-risk AI systems as regards risk management,
    the quality and relevance of data sets used, technical documentation and record-keeping,
    transparency and the provision of information to deployers, human oversight, and
    robustness, accuracy and cybersecurity. Those requirements are necessary to effectively
    mitigate the risks for health, safety and fundamental rights. As no other less
    trade restrictive measures are reasonably available those requirements are not
    unjustified restrictions to trade.













    (67)'
- source_sentence: What criteria determine whether an AI system used in the administration
    of justice is classified as high-risk?
  sentences:
  - which one or more of the following conditions are fulfilled. The first such condition
    should be that the AI system is intended to perform a narrow procedural task,
    such as an AI system that transforms unstructured data into structured data, an
    AI system that classifies incoming documents into categories or an AI system that
    is used to detect duplicates among a large number of applications. Those tasks
    are of such narrow and limited nature that they pose only limited risks which
    are not increased through the use of an AI system in a context that is listed
    as a high-risk use in an annex to this Regulation. The second condition should
    be that the task performed by the AI system is intended to improve the result
    of a previously completed human
  - Certain AI systems intended for the administration of justice and democratic processes
    should be classified as high-risk, considering their potentially significant impact
    on democracy, the rule of law, individual freedoms as well as the right to an
    effective remedy and to a fair trial. In particular, to address the risks of potential
    biases, errors and opacity, it is appropriate to qualify as high-risk AI systems
    intended to be used by a judicial authority or on its behalf to assist judicial
    authorities in researching and interpreting facts and the law and in applying
    the law to a concrete set of facts. AI systems intended to be used by alternative
    dispute resolution bodies for those purposes should also be considered to be high-risk
    when
  - As regards AI systems that are safety components of products, or which are themselves
    products, falling within the scope of certain Union harmonisation legislation
    listed in an annex to this Regulation, it is appropriate to classify them as high-risk
    under this Regulation if the product concerned undergoes the conformity assessment
    procedure with a third-party conformity assessment body pursuant to that relevant
    Union harmonisation legislation. In particular, such products are machinery, toys,
    lifts, equipment and protective systems intended for use in potentially explosive
    atmospheres, radio equipment, pressure equipment, recreational craft equipment,
    cableway installations, appliances burning gaseous fuels, medical devices, in
    vitro
pipeline_tag: sentence-similarity
library_name: sentence-transformers
metrics:
- cosine_accuracy@1
- cosine_accuracy@3
- cosine_accuracy@5
- cosine_accuracy@10
- cosine_precision@1
- cosine_precision@3
- cosine_precision@5
- cosine_precision@10
- cosine_recall@1
- cosine_recall@3
- cosine_recall@5
- cosine_recall@10
- cosine_ndcg@10
- cosine_mrr@10
- cosine_map@100
model-index:
- name: SentenceTransformer based on Snowflake/snowflake-arctic-embed-l
  results:
  - task:
      type: information-retrieval
      name: Information Retrieval
    dataset:
      name: Unknown
      type: unknown
    metrics:
    - type: cosine_accuracy@1
      value: 0.9583333333333334
      name: Cosine Accuracy@1
    - type: cosine_accuracy@3
      value: 1.0
      name: Cosine Accuracy@3
    - type: cosine_accuracy@5
      value: 1.0
      name: Cosine Accuracy@5
    - type: cosine_accuracy@10
      value: 1.0
      name: Cosine Accuracy@10
    - type: cosine_precision@1
      value: 0.9583333333333334
      name: Cosine Precision@1
    - type: cosine_precision@3
      value: 0.3333333333333333
      name: Cosine Precision@3
    - type: cosine_precision@5
      value: 0.19999999999999998
      name: Cosine Precision@5
    - type: cosine_precision@10
      value: 0.09999999999999999
      name: Cosine Precision@10
    - type: cosine_recall@1
      value: 0.9583333333333334
      name: Cosine Recall@1
    - type: cosine_recall@3
      value: 1.0
      name: Cosine Recall@3
    - type: cosine_recall@5
      value: 1.0
      name: Cosine Recall@5
    - type: cosine_recall@10
      value: 1.0
      name: Cosine Recall@10
    - type: cosine_ndcg@10
      value: 0.9791666666666666
      name: Cosine Ndcg@10
    - type: cosine_mrr@10
      value: 0.9722222222222223
      name: Cosine Mrr@10
    - type: cosine_map@100
      value: 0.9722222222222222
      name: Cosine Map@100
---

# Sleem247/legal-ft-1-Q8_0-GGUF
This model was converted to GGUF format from [`llm-wizard/legal-ft-1`](https://huggingface.co/llm-wizard/legal-ft-1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/llm-wizard/legal-ft-1) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
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:
```bash
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](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) 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
```