A large language model that can use text prompts to generate and discuss code.
7B
13B
34B
70B
499.3K Pulls Updated 3 weeks ago
code
3.8GB
instruct
3.8GB
python
3.8GB
70b-code
39GB
70b-instruct
39GB
70b-python
39GB
70b-code-q4_0
39GB
70b-code-q4_1
43GB
70b-code-q5_0
47GB
70b-code-q5_1
52GB
70b-code-q8_0
73GB
70b-code-q2_K
25GB
70b-code-q3_K_S
30GB
70b-code-q3_K_M
33GB
70b-code-q3_K_L
36GB
70b-code-q4_K_S
39GB
70b-code-q4_K_M
41GB
70b-code-q5_K_S
47GB
70b-code-q5_K_M
49GB
70b-code-q6_K
57GB
70b-code-fp16
138GB
70b-instruct-q4_0
39GB
70b-instruct-q4_1
43GB
70b-instruct-q5_0
47GB
70b-instruct-q5_1
52GB
70b-instruct-q8_0
73GB
70b-instruct-q2_K
25GB
70b-instruct-q3_K_S
30GB
70b-instruct-q3_K_M
33GB
70b-instruct-q3_K_L
36GB
70b-instruct-q4_K_S
39GB
70b-instruct-q4_K_M
41GB
70b-instruct-q5_K_S
47GB
70b-instruct-q5_K_M
49GB
70b-instruct-q6_K
57GB
70b-instruct-fp16
138GB
70b-python-q4_0
39GB
70b-python-q4_1
43GB
70b-python-q5_0
47GB
70b-python-q5_1
52GB
70b-python-q8_0
73GB
70b-python-q2_K
25GB
70b-python-q3_K_S
30GB
70b-python-q3_K_M
33GB
70b-python-q3_K_L
36GB
70b-python-q4_K_S
39GB
70b-python-q4_K_M
41GB
70b-python-q5_K_S
47GB
70b-python-q5_K_M
49GB
70b-python-q6_K
57GB
70b-python-fp16
138GB
34b-code
19GB
34b-instruct
19GB
34b-python
19GB
34b-code-q4_0
19GB
34b-code-q4_1
21GB
34b-code-q5_0
23GB
34b-code-q5_1
25GB
34b-code-q8_0
36GB
34b-code-q2_K
14GB
34b-code-q3_K_S
15GB
34b-code-q3_K_M
16GB
34b-code-q3_K_L
18GB
34b-code-q4_K_S
19GB
34b-code-q4_K_M
20GB
34b-code-q5_K_S
23GB
34b-code-q5_K_M
24GB
34b-code-q6_K
28GB
34b-instruct-q4_0
19GB
34b-instruct-q4_1
21GB
34b-instruct-q5_0
23GB
34b-instruct-q5_1
25GB
34b-instruct-q8_0
36GB
34b-instruct-q2_K
14GB
34b-instruct-q3_K_S
15GB
34b-instruct-q3_K_M
16GB
34b-instruct-q3_K_L
18GB
34b-instruct-q4_K_S
19GB
34b-instruct-q4_K_M
20GB
34b-instruct-q5_K_S
23GB
34b-instruct-q5_K_M
24GB
34b-instruct-q6_K
28GB
34b-instruct-fp16
67GB
34b-python-q4_0
19GB
34b-python-q4_1
21GB
34b-python-q5_0
23GB
34b-python-q5_1
25GB
34b-python-q8_0
36GB
34b-python-q2_K
14GB
34b-python-q3_K_S
15GB
34b-python-q3_K_M
16GB
34b-python-q3_K_L
18GB
34b-python-q4_K_S
19GB
34b-python-q4_K_M
20GB
34b-python-q5_K_S
23GB
34b-python-q5_K_M
24GB
34b-python-q6_K
28GB
34b-python-fp16
67GB
13b-code
7.4GB
13b-instruct
7.4GB
13b-python
7.4GB
13b-code-q4_0
7.4GB
13b-code-q4_1
8.2GB
13b-code-q5_0
9.0GB
13b-code-q5_1
9.8GB
13b-code-q8_0
14GB
13b-code-q2_K
5.4GB
13b-code-q3_K_S
5.7GB
13b-code-q3_K_M
6.3GB
13b-code-q3_K_L
6.9GB
13b-code-q4_K_S
7.4GB
13b-code-q4_K_M
7.9GB
13b-code-q5_K_S
9.0GB
13b-code-q5_K_M
9.2GB
13b-code-q6_K
11GB
13b-code-fp16
26GB
13b-instruct-q4_0
7.4GB
13b-instruct-q4_1
8.2GB
13b-instruct-q5_0
9.0GB
13b-instruct-q5_1
9.8GB
13b-instruct-q8_0
14GB
13b-instruct-q2_K
5.4GB
13b-instruct-q3_K_S
5.7GB
13b-instruct-q3_K_M
6.3GB
13b-instruct-q3_K_L
6.9GB
13b-instruct-q4_K_S
7.4GB
13b-instruct-q4_K_M
7.9GB
13b-instruct-q5_K_S
9.0GB
13b-instruct-q5_K_M
9.2GB
13b-instruct-q6_K
11GB
13b-instruct-fp16
26GB
13b-python-q4_0
7.4GB
13b-python-q4_1
8.2GB
13b-python-q5_0
9.0GB
13b-python-q5_1
9.8GB
13b-python-q8_0
14GB
13b-python-q2_K
5.4GB
13b-python-q3_K_S
5.7GB
13b-python-q3_K_M
6.3GB
13b-python-q3_K_L
6.9GB
13b-python-q4_K_S
7.4GB
13b-python-q4_K_M
7.9GB
13b-python-q5_K_S
9.0GB
13b-python-q5_K_M
9.2GB
13b-python-q6_K
11GB
13b-python-fp16
26GB
7b-code
3.8GB
7b-instruct
3.8GB
7b-python
3.8GB
7b-code-q4_0
3.8GB
7b-code-q4_1
4.2GB
7b-code-q5_0
4.7GB
7b-code-q5_1
5.1GB
7b-code-q8_0
7.2GB
7b-code-q2_K
2.8GB
7b-code-q3_K_S
2.9GB
7b-code-q3_K_M
3.3GB
7b-code-q3_K_L
3.6GB
7b-code-q4_K_S
3.9GB
7b-code-q4_K_M
4.1GB
7b-code-q5_K_S
4.7GB
7b-code-q5_K_M
4.8GB
7b-code-q6_K
5.5GB
7b-code-fp16
13GB
7b-instruct-q4_0
3.8GB
7b-instruct-q4_1
4.2GB
7b-instruct-q5_0
4.7GB
7b-instruct-q5_1
5.1GB
7b-instruct-q8_0
7.2GB
7b-instruct-q2_K
2.8GB
7b-instruct-q3_K_S
2.9GB
7b-instruct-q3_K_M
3.3GB
7b-instruct-q3_K_L
3.6GB
7b-instruct-q4_K_S
3.9GB
7b-instruct-q4_K_M
4.1GB
7b-instruct-q5_K_S
4.7GB
7b-instruct-q5_K_M
4.8GB
7b-instruct-q6_K
5.5GB
7b-instruct-fp16
13GB
7b-python-q4_0
3.8GB
7b-python-q4_1
4.2GB
7b-python-q5_0
4.7GB
7b-python-q5_1
5.1GB
7b-python-q8_0
7.2GB
7b-python-q2_K
2.8GB
7b-python-q3_K_S
2.9GB
7b-python-q3_K_M
3.3GB
7b-python-q3_K_L
3.6GB
7b-python-q4_K_S
3.9GB
7b-python-q4_K_M
4.1GB
7b-python-q5_K_S
4.7GB
7b-python-q5_K_M
4.8GB
7b-python-q6_K
5.5GB
7b-python-fp16
13GB
590d74a5569b · 4.8kB
# Llama Code Acceptable Use Policy
Meta is committed to promoting safe and fair use of its tools and features, including Llama Code. If you access or use Llama Code, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at [ai.meta.com/llama/use-policy](http://ai.meta.com/llama/use-policy).
## Prohibited Uses
We want everyone to use Llama Code safely and responsibly. You agree you will not use, or allow others to use, Llama Code to:
1. Violate the law or others’ rights, including to:
1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
1. Violence or terrorism
2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
3. Human trafficking, exploitation, and sexual violence
4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
5. Sexual solicitation
6. Any other criminal activity
2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
3. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
5. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
6. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama 2 Materials
7. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama Code related to the following:
1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
2. Guns and illegal weapons (including weapon development)
3. Illegal drugs and regulated/controlled substances
4. Operation of critical infrastructure, transportation technologies, or heavy machinery
5. Self-harm or harm to others, including suicide, cutting, and eating disorders
6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
3. Intentionally deceive or mislead others, including use of Llama Code related to the following:
1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
3. Generating, promoting, or further distributing spam
4. Impersonating another individual without consent, authorization, or legal right
5. Representing that the use of Llama Code or outputs are human-generated
6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
4. Fail to appropriately disclose to end users any known dangers of your AI system
Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:
* Reporting issues with the model: [github.com/facebookresearch/llama](http://github.com/facebookresearch/llama)
* Reporting risky content generated by the model: [developers.facebook.com/llama_output_feedback](http://developers.facebook.com/llama_output_feedback)
* Reporting bugs and security concerns: [facebook.com/whitehat/info](http://facebook.com/whitehat/info)
* Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama: [LlamaUseReport@meta.com](mailto:LlamaUseReport@meta.com)