General use chat model based on Llama and Llama 2 with 2K to 16K context sizes.
48.7K Pulls Updated 6 months ago
33b-q4_0
18GB
33b-q4_1
20GB
33b-q5_0
22GB
33b-q5_1
24GB
33b-q8_0
35GB
33b-q2_K
14GB
33b-q3_K_S
14GB
33b-q3_K_M
16GB
33b-q3_K_L
17GB
33b-q4_K_S
18GB
33b-q4_K_M
20GB
33b-q5_K_S
22GB
33b-q5_K_M
23GB
33b-q6_K
27GB
33b-fp16
65GB
13b-16k
7.4GB
13b-q4_0
7.4GB
13b-q4_1
8.2GB
13b-q5_0
9.0GB
13b-q5_1
9.8GB
13b-q8_0
14GB
13b-q2_K
5.4GB
13b-q3_K_S
5.7GB
13b-q3_K_M
6.3GB
13b-q3_K_L
6.9GB
13b-q4_K_S
7.4GB
13b-q4_K_M
7.9GB
13b-q5_K_S
9.0GB
13b-q5_K_M
9.2GB
13b-q6_K
11GB
13b-fp16
26GB
13b-v1.5-q4_0
7.4GB
13b-v1.5-q4_1
8.2GB
13b-v1.5-q5_0
9.0GB
13b-v1.5-q5_1
9.8GB
13b-v1.5-q8_0
14GB
13b-v1.5-q2_K
5.4GB
13b-v1.5-q3_K_S
5.7GB
13b-v1.5-q3_K_M
6.3GB
13b-v1.5-q3_K_L
6.9GB
13b-v1.5-q4_K_S
7.4GB
13b-v1.5-q4_K_M
7.9GB
13b-v1.5-q5_K_S
9.0GB
13b-v1.5-q5_K_M
9.2GB
13b-v1.5-q6_K
11GB
13b-v1.5-fp16
26GB
13b-v1.5-16k-q4_0
7.4GB
13b-v1.5-16k-q4_1
8.2GB
13b-v1.5-16k-q5_0
9.0GB
13b-v1.5-16k-q5_1
9.8GB
13b-v1.5-16k-q8_0
14GB
13b-v1.5-16k-q2_K
5.4GB
13b-v1.5-16k-q3_K_S
5.7GB
13b-v1.5-16k-q3_K_M
6.3GB
13b-v1.5-16k-q3_K_L
6.9GB
13b-v1.5-16k-q4_K_S
7.4GB
13b-v1.5-16k-q4_K_M
7.9GB
13b-v1.5-16k-q5_K_S
9.0GB
13b-v1.5-16k-q5_K_M
9.2GB
13b-v1.5-16k-q6_K
11GB
13b-v1.5-16k-fp16
26GB
7b-16k
3.8GB
7b-q4_0
3.8GB
7b-q4_1
4.2GB
7b-q5_0
4.7GB
7b-q5_1
5.1GB
7b-q8_0
7.2GB
7b-q2_K
2.8GB
7b-q3_K_S
2.9GB
7b-q3_K_M
3.3GB
7b-q3_K_L
3.6GB
7b-q4_K_S
3.9GB
7b-q4_K_M
4.1GB
7b-q5_K_S
4.7GB
7b-q5_K_M
4.8GB
7b-q6_K
5.5GB
7b-fp16
13GB
7b-v1.5-q4_0
3.8GB
7b-v1.5-q4_1
4.2GB
7b-v1.5-q5_0
4.7GB
7b-v1.5-q5_1
5.1GB
7b-v1.5-q8_0
7.2GB
7b-v1.5-q2_K
2.8GB
7b-v1.5-q3_K_S
2.9GB
7b-v1.5-q3_K_M
3.3GB
7b-v1.5-q3_K_L
3.6GB
7b-v1.5-q4_K_S
3.9GB
7b-v1.5-q4_K_M
4.1GB
7b-v1.5-q5_K_S
4.7GB
7b-v1.5-q5_K_M
4.8GB
7b-v1.5-q6_K
5.5GB
7b-v1.5-fp16
13GB
7b-v1.5-16k-q4_0
3.8GB
7b-v1.5-16k-q4_1
4.2GB
7b-v1.5-16k-q5_0
4.7GB
7b-v1.5-16k-q5_1
5.1GB
7b-v1.5-16k-q8_0
7.2GB
7b-v1.5-16k-q2_K
2.8GB
7b-v1.5-16k-q3_K_S
2.9GB
7b-v1.5-16k-q3_K_M
3.3GB
7b-v1.5-16k-q3_K_L
3.6GB
7b-v1.5-16k-q4_K_S
3.9GB
7b-v1.5-16k-q4_K_M
4.1GB
7b-v1.5-16k-q5_K_S
4.7GB
7b-v1.5-16k-q5_K_M
4.8GB
7b-v1.5-16k-q6_K
5.5GB
7b-v1.5-16k-fp16
13GB
Updated 6 months ago
6 months ago
370739dc897b · 3.8GB
model
archllama
·
parameters7B
·
quantization4-bit
3.8GB
system
A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
155B
template
{{ .System }}
USER: {{ .Prompt }}
ASSISTANT:
45B
params
{"stop":["USER:","ASSISTANT:"]}
31B
Readme
Vicuna is a chat assistant model. It includes 3 different variants in 3 different sizes. v1.3 is trained by fine-tuning Llama and has a context size of 2048 tokens. v1.5 is trained by fine-tuning Llama 2 and has a context size of 2048 tokens. v1.5-16k is trained by fine-tuning Llama 2 and has a context size of 16k tokens. All three variants are trained using conversations collected from ShareGPT.
Example prompts
What is the meaning of life? Explain it in 5 paragraphs.