
These are quantized ggml binary files for vicuna 7B and 13B models. The version of vicuna for these models are v0.

These files can be used in conjunction with minigpt4 ggml models [7B](https://huggingface.co/datasets/maknee/minigpt4-7b-ggml) and [13B](https://huggingface.co/datasets/maknee/minigpt4-13b-ggml) in [minigpt4.cpp](https://github.com/Maknee/minigpt4.cpp)

Recommended are the Q5_K and Q6_K implementations. If there are any issues, use Q4_1 or Q4_0.

---

# Vicuna Model Card

## Model details

**Model type:**
Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
It is an auto-regressive language model, based on the transformer architecture.

**Model date:**
Vicuna was trained between March 2023 and April 2023.

**Organizations developing the model:**
The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.

**Paper or resources for more information:**
https://vicuna.lmsys.org/

**License:**
Apache License 2.0

**Where to send questions or comments about the model:**
https://github.com/lm-sys/FastChat/issues

## Intended use
**Primary intended uses:**
The primary use of Vicuna is research on large language models and chatbots.

**Primary intended users:**
The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.

## Training dataset
70K conversations collected from ShareGPT.com.
(48k for the uncensored variant. 22k worth of garbage removed – see https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered)

## Evaluation dataset
A preliminary evaluation of the model quality is conducted by creating a set of 80 diverse questions and utilizing GPT-4 to judge the model outputs. See https://vicuna.lmsys.org/ for more details.

language:en language:bg language:ca language:cs language:da language:de language:es language:fr language:hr language:hu language:it language:nl language:pl language:pt language:ro language:ru language:sl language:sr language:sv language:uk license:apache-2.0 vicuna vicuna-v0 ggml region:us
{"language": ["en", "bg", "ca", "cs", "da", "de", "es", "fr", "hr", "hu", "it", "nl", "pl", "pt", "ro", "ru", "sl", "sr", "sv", "uk"], "license": "apache-2.0", "tags": ["vicuna", "vicuna-v0", "ggml"], "pipeline_tag": "conversational", "library_name": "adapter-transformers"}
TAGS
#language-English #language-Bulgarian #language-Catalan #language-Czech #language-Danish #language-German #language-Spanish #language-French #language-Croatian #language-Hungarian #language-Italian #language-Dutch #language-Polish #language-Portuguese #language-Romanian #language-Russian #language-Slovenian #language-Serbian #language-Swedish #language-Ukrainian #license-apache-2.0 #vicuna #vicuna-v0 #ggml #region-us 


These are quantized ggml binary files for vicuna 7B and 13B models. The version of vicuna for these models are v0.

These files can be used in conjunction with minigpt4 ggml models 7B and 13B in URL

Recommended are the Q5_K and Q6_K implementations. If there are any issues, use Q4_1 or Q4_0.

---

# Vicuna Model Card

## Model details

Model type:
Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
It is an auto-regressive language model, based on the transformer architecture.

Model date:
Vicuna was trained between March 2023 and April 2023.

Organizations developing the model:
The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.

Paper or resources for more information:
URL

License:
Apache License 2.0

Where to send questions or comments about the model:
URL

## Intended use
Primary intended uses:
The primary use of Vicuna is research on large language models and chatbots.

Primary intended users:
The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.

## Training dataset
70K conversations collected from URL.
(48k for the uncensored variant. 22k worth of garbage removed – see URL

## Evaluation dataset
A preliminary evaluation of the model quality is conducted by creating a set of 80 diverse questions and utilizing GPT-4 to judge the model outputs. See URL for more details.

# Vicuna Model Card ## Model details

Model type:
Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
It is an auto-regressive language model, based on the transformer architecture.

Model date:
Vicuna was trained between March 2023 and April 2023.

Organizations developing the model:
The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.

Paper or resources for more information:
URL

License:
Apache License 2.0

Where to send questions or comments about the model:
URL ## Intended use
Primary intended uses:
The primary use of Vicuna is research on large language models and chatbots.

Primary intended users:
The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence. ## Training dataset
70K conversations collected from URL.
(48k for the uncensored variant. 22k worth of garbage removed – see URL ## Evaluation dataset
A preliminary evaluation of the model quality is conducted by creating a set of 80 diverse questions and utilizing GPT-4 to judge the model outputs. See URL for more details.
TAGS
#language-English #language-Bulgarian #language-Catalan #language-Czech #language-Danish #language-German #language-Spanish #language-French #language-Croatian #language-Hungarian #language-Italian #language-Dutch #language-Polish #language-Portuguese #language-Romanian #language-Russian #language-Slovenian #language-Serbian #language-Swedish #language-Ukrainian #license-apache-2.0 #vicuna #vicuna-v0 #ggml #region-us 
 # Vicuna Model Card ## Model details

Model type:
Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
It is an auto-regressive language model, based on the transformer architecture.

Model date:
Vicuna was trained between March 2023 and April 2023.

Organizations developing the model:
The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.

Paper or resources for more information:
URL

License:
Apache License 2.0

Where to send questions or comments about the model:
URL ## Intended use
Primary intended uses:
The primary use of Vicuna is research on large language models and chatbots.

Primary intended users:
The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence. ## Training dataset
70K conversations collected from URL.
(48k for the uncensored variant. 22k worth of garbage removed – see URL ## Evaluation dataset
A preliminary evaluation of the model quality is conducted by creating a set of 80 diverse questions and utilizing GPT-4 to judge the model outputs. See URL for more details.
passage: TAGS
#language-English #language-Bulgarian #language-Catalan #language-Czech #language-Danish #language-German #language-Spanish #language-French #language-Croatian #language-Hungarian #language-Italian #language-Dutch #language-Polish #language-Portuguese #language-Romanian #language-Russian #language-Slovenian #language-Serbian #language-Swedish #language-Ukrainian #license-apache-2.0 #vicuna #vicuna-v0 #ggml #region-us 
# Vicuna Model Card## Model details

Model type:
Vicuna is an open-source chatbot trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.
It is an auto-regressive language model, based on the transformer architecture.

Model date:
Vicuna was trained between March 2023 and April 2023.

Organizations developing the model:
The Vicuna team with members from UC Berkeley, CMU, Stanford, and UC San Diego.

Paper or resources for more information:
URL

License:
Apache License 2.0

Where to send questions or comments about the model:
URL## Intended use
Primary intended uses:
The primary use of Vicuna is research on large language models and chatbots.

Primary intended users:
The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.## Training dataset
70K conversations collected from URL.
(48k for the uncensored variant. 22k worth of garbage removed – see URL## Evaluation dataset
A preliminary evaluation of the model quality is conducted by creating a set of 80 diverse questions and utilizing GPT-4 to judge the model outputs. See URL for more details.