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RichardErkhov/
llmat_-_Mistral-v0.3-7B-ORPO-gguf

Name: llmat_-_Mistral-v0.3-7B-ORPO-gguf
Availability: InStock

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Mistral-v0.3-7B-ORPO - GGUF

Model creator: https://huggingface.co/llmat/
Original model: https://huggingface.co/llmat/Mistral-v0.3-7B-ORPO/

Name	Quant method	Size
Mistral-v0.3-7B-ORPO.Q2_K.gguf	Q2_K	2.54GB
Mistral-v0.3-7B-ORPO.IQ3_XS.gguf	IQ3_XS	2.82GB
Mistral-v0.3-7B-ORPO.IQ3_S.gguf	IQ3_S	2.97GB
Mistral-v0.3-7B-ORPO.Q3_K_S.gguf	Q3_K_S	2.95GB
Mistral-v0.3-7B-ORPO.IQ3_M.gguf	IQ3_M	3.06GB
Mistral-v0.3-7B-ORPO.Q3_K.gguf	Q3_K	3.28GB
Mistral-v0.3-7B-ORPO.Q3_K_M.gguf	Q3_K_M	3.28GB
Mistral-v0.3-7B-ORPO.Q3_K_L.gguf	Q3_K_L	3.56GB
Mistral-v0.3-7B-ORPO.IQ4_XS.gguf	IQ4_XS	3.68GB
Mistral-v0.3-7B-ORPO.Q4_0.gguf	Q4_0	3.83GB
Mistral-v0.3-7B-ORPO.IQ4_NL.gguf	IQ4_NL	3.87GB
Mistral-v0.3-7B-ORPO.Q4_K_S.gguf	Q4_K_S	3.86GB
Mistral-v0.3-7B-ORPO.Q4_K.gguf	Q4_K	3.87GB
Mistral-v0.3-7B-ORPO.Q4_K_M.gguf	Q4_K_M	3.87GB
Mistral-v0.3-7B-ORPO.Q4_1.gguf	Q4_1	3.87GB
Mistral-v0.3-7B-ORPO.Q5_0.gguf	Q5_0	3.87GB
Mistral-v0.3-7B-ORPO.Q5_K_S.gguf	Q5_K_S	3.87GB
Mistral-v0.3-7B-ORPO.Q5_K.gguf	Q5_K	3.87GB
Mistral-v0.3-7B-ORPO.Q5_K_M.gguf	Q5_K_M	3.87GB
Mistral-v0.3-7B-ORPO.Q5_1.gguf	Q5_1	3.87GB
Mistral-v0.3-7B-ORPO.Q6_K.gguf	Q6_K	3.87GB
Mistral-v0.3-7B-ORPO.Q8_0.gguf	Q8_0	3.87GB

Original model description:

base_model: unsloth/mistral-7b-v0.3-bnb-4bit language:

en license: apache-2.0 tags:
text-generation-inference
transformers
unsloth
mistral
trl
orpo

Uploaded model

Developed by: llmat
License: apache-2.0
Finetuned from model : unsloth/mistral-7b-v0.3-bnb-4bit

This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.

💻 Usage

python

!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "llmat/Mistral-v0.3-7B-ORPO"
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"])

RichardErkhov/llmat_-_Mistral-v0.3-7B-ORPO-gguf

Original model description:

Uploaded model

💻 Usage

RichardErkhov/
llmat_-_Mistral-v0.3-7B-ORPO-gguf