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RichardErkhov/
Pection_-_llama3-finetune-gguf

Name: Pection_-_llama3-finetune-gguf
Availability: InStock

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gguf

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llama3-finetune - GGUF

Model creator: https://huggingface.co/Pection/
Original model: https://huggingface.co/Pection/llama3-finetune/

Name	Quant method	Size
llama3-finetune.Q2_K.gguf	Q2_K	0.54GB
llama3-finetune.IQ3_XS.gguf	IQ3_XS	0.58GB
llama3-finetune.IQ3_S.gguf	IQ3_S	0.6GB
llama3-finetune.Q3_K_S.gguf	Q3_K_S	0.6GB
llama3-finetune.IQ3_M.gguf	IQ3_M	0.61GB
llama3-finetune.Q3_K.gguf	Q3_K	0.64GB
llama3-finetune.Q3_K_M.gguf	Q3_K_M	0.64GB
llama3-finetune.Q3_K_L.gguf	Q3_K_L	0.68GB
llama3-finetune.IQ4_XS.gguf	IQ4_XS	0.7GB
llama3-finetune.Q4_0.gguf	Q4_0	0.72GB
llama3-finetune.IQ4_NL.gguf	IQ4_NL	0.72GB
llama3-finetune.Q4_K_S.gguf	Q4_K_S	0.72GB
llama3-finetune.Q4_K.gguf	Q4_K	0.75GB
llama3-finetune.Q4_K_M.gguf	Q4_K_M	0.75GB
llama3-finetune.Q4_1.gguf	Q4_1	0.77GB
llama3-finetune.Q5_0.gguf	Q5_0	0.83GB
llama3-finetune.Q5_K_S.gguf	Q5_K_S	0.83GB
llama3-finetune.Q5_K.gguf	Q5_K	0.85GB
llama3-finetune.Q5_K_M.gguf	Q5_K_M	0.85GB
llama3-finetune.Q5_1.gguf	Q5_1	0.89GB
llama3-finetune.Q6_K.gguf	Q6_K	0.95GB
llama3-finetune.Q8_0.gguf	Q8_0	1.23GB

Original model description:

language:

en
th library_name: transformers base_model:
meta-llama/Llama-3.2-1B tags:
- text-generation pipeline_tag: text-generation inference: parameters: temperature: 0.5 widget:
messages:
- role: user content: What is your favorite condiment?

extra_gated_description: If you want to learn more about how we process your personal data, please read our Privacy Policy.

LLaMA 3 Fine-Tuned Model

This is a fine-tuned version of the LLaMA 3 model . Below is an example of how to use it:

Example Usage

python

from transformers import AutoModelForCausalLM, AutoTokenizer

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained("Pection/llama3-finetune")
model = AutoModelForCausalLM.from_pretrained("Pection/llama3-finetune")

# Generate response
prompt = "Where is Bangkok?"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)

print(response)

RichardErkhov/Pection_-_llama3-finetune-gguf

Original model description:

extra_gated_description: If you want to learn more about how we process your personal data, please read our Privacy Policy.

LLaMA 3 Fine-Tuned Model

Example Usage

RichardErkhov/
Pection_-_llama3-finetune-gguf