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KaraKaraWitch_-_L3.1-70b-Inori-gguf
RichardErkhov/KaraKaraWitch_-_L3.1-70b-Inori-gguf
KaraKaraWitch_-_L3.1-70b-Inori-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf926 GB · 100%
At a glance
- Access
- Public
- Created
- Sep 8, 2024
- Updated
- Sep 9, 2024
- SHA
- 1d9a96fa
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
L3.1-70b-Inori - GGUF
- Model creator: https://huggingface.co/KaraKaraWitch/
- Original model: https://huggingface.co/KaraKaraWitch/L3.1-70b-Inori/
| Name | Quant method | Size |
|---|---|---|
| L3.1-70b-Inori.Q2_K.gguf | Q2_K | 24.56GB |
| L3.1-70b-Inori.IQ3_XS.gguf | IQ3_XS | 27.29GB |
| L3.1-70b-Inori.IQ3_S.gguf | IQ3_S | 28.79GB |
| L3.1-70b-Inori.Q3_K_S.gguf | Q3_K_S | 28.79GB |
| L3.1-70b-Inori.IQ3_M.gguf | IQ3_M | 29.74GB |
| L3.1-70b-Inori.Q3_K.gguf | Q3_K | 31.91GB |
| L3.1-70b-Inori.Q3_K_M.gguf | Q3_K_M | 31.91GB |
| L3.1-70b-Inori.Q3_K_L.gguf | Q3_K_L | 34.59GB |
| L3.1-70b-Inori.IQ4_XS.gguf | IQ4_XS | 35.64GB |
| L3.1-70b-Inori.Q4_0.gguf | Q4_0 | 37.22GB |
| L3.1-70b-Inori.IQ4_NL.gguf | IQ4_NL | 37.58GB |
| L3.1-70b-Inori.Q4_K_S.gguf | Q4_K_S | 37.58GB |
| L3.1-70b-Inori.Q4_K.gguf | Q4_K | 39.6GB |
| L3.1-70b-Inori.Q4_K_M.gguf | Q4_K_M | 39.6GB |
| L3.1-70b-Inori.Q4_1.gguf | Q4_1 | 41.27GB |
| L3.1-70b-Inori.Q5_0.gguf | Q5_0 | 45.32GB |
| L3.1-70b-Inori.Q5_K_S.gguf | Q5_K_S | 45.32GB |
| L3.1-70b-Inori.Q5_K.gguf | Q5_K | 46.52GB |
| L3.1-70b-Inori.Q5_K_M.gguf | Q5_K_M | 46.52GB |
| L3.1-70b-Inori.Q5_1.gguf | Q5_1 | 49.36GB |
| L3.1-70b-Inori.Q6_K.gguf | Q6_K | 53.91GB |
| L3.1-70b-Inori.Q8_0.gguf | Q8_0 | 69.83GB |
Original model description:
base_model:
- abacusai/Dracarys-Llama-3.1-70B-Instruct
- Sao10K/L3-70B-Euryale-v2.1
- gbueno86/Cathallama-70B
- sophosympatheia/New-Dawn-Llama-3.1-70B-v1.1
- nothingiisreal/L3.1-70B-Celeste-V0.1-BF16
- Fizzarolli/L3.1-70b-glitz-v0.2
- cyberagent/Llama-3.1-70B-Japanese-Instruct-2407 library_name: transformers tags:
- mergekit
- merge
- abacusai/Dracarys-Llama-3.1-70B-Instruct
- Sao10K/L3-70B-Euryale-v2.1
- gbueno86/Cathallama-70B
- sophosympatheia/New-Dawn-Llama-3.1-70B-v1.1
- nothingiisreal/L3.1-70B-Celeste-V0.1-BF16
- Fizzarolli/L3.1-70b-glitz-v0.2
- cyberagent/Llama-3.1-70B-Japanese-Instruct-2407
KaraKaraWitch/L3.1-70b-Inori
Inori is the second 70b for the weekend for me to play around.
Learning from the previous model, I yeeted Hermes into the atmosphere and used Glitz as a base.
Inori takes a different approach by using Model Stock.
- Dracarys (I just threw it in, but can be useful for code)
- Euryale (You all know it!)
- Cathallama (Athene + turboderp_cat)
- New Dawn (I heard people like it so I added it in)
- Celeste (RP)
- Japanese-Instruct (Enhancement of Japanese Language for the weebs out there.)
No Hermes was harmed in the making of this model stock merge.
L3.1-70b-Inori is a merge of the following models using LazyMergekit:
- abacusai/Dracarys-Llama-3.1-70B-Instruct
- Sao10K/L3-70B-Euryale-v2.1
- gbueno86/Cathallama-70B
- sophosympatheia/New-Dawn-Llama-3.1-70B-v1.1
- nothingiisreal/L3.1-70B-Celeste-V0.1-BF16
- cyberagent/Llama-3.1-70B-Japanese-Instruct-2407
General Thoughts
- This model has some weird censorship issues. Soketimes it triggers that it can't generate explicit text while sometimes it doesn't.
- For that reason, I don't recommend people to use this model.
Yap / Chat Format
L3 Instruct.
Quants & Hosts
🧩 Configuration
models:
- model: Fizzarolli/L3.1-70b-glitz-v0.2
- model: cyberagent/Llama-3.1-70B-Japanese-Instruct-2407
- model: Sao10K/L3-70B-Euryale-v2.1
- model: nothingiisreal/L3.1-70B-Celeste-V0.1-BF16
- model: sophosympatheia/New-Dawn-Llama-3.1-70B-v1.1
- model: gbueno86/Cathallama-70B
- model: abacusai/Dracarys-Llama-3.1-70B-Instruct
merge_method: model_stock
base_model: Fizzarolli/L3.1-70b-glitz-v0.2
parameters:
normalize: true
dtype: bfloat16
💻 Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "KaraKaraWitch/L3.1-70b-Inori"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
- Created
- Sep 8, 2024
- Updated
- Sep 9, 2024