Hugging Face model: clarkkitchen22/mistral-7b-lora-merged
Author: clarkkitchen22
Created: 2025-11-10 00:21:05
Last modified: 2025-11-12 16:43:05
Pipeline: text-generation
Library: transformers
Likes: 1 | Downloads: 5
Tags: transformers, safetensors, mistral, text-generation, conversational, en, license:apache-2.0, text-generation-inference, endpoints_compatible, region:us
Card metadata:
model_name: Mistral-7B-LoRA-Merged
repo: clarkkitchen22/mistral-7b-lora-merged
author: clarkkitchen22
license: apache-2.0
language: en
library_name: transformers
pipeline_tag: text-generation
base_model: mistralai/Mistral-7B
quantization: supported: fp16, 4bit-bnb, 8bit-bnb
recommended: 4bit-bnb
notes: Runs on RTX 2070 (8GB) with bitsandbytes.
training: approach: LoRA (Low-Rank Adaptation)
lora: rank_r: 16
alpha: 32
dropout: 0.05
target_modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
hardware: gpu: RTX 2070 (8GB)
cpu: Intel i7-9750H
ram_gb: 16
timeframe: Developed over a single weekend (self-taught; no prior Python experience)
chat_template: style: 
 ... 

bos_token: 

eos_token: 

metrics: name: qualitative_instruction_following
value: good
notes: Tested manually across diverse prompts; no formal benchmark., name: latency
value: device-dependent
notes: Merged weights enable faster load times and simplified inference.
usage: quickstart: from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "clarkkitchen22/mistral-7b-lora-merged"
tok = AutoTokenizer.from_pretrained(model_id)
mdl = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", torch_dtype=torch.float16)
x = tok("Explain LoRA in simple terms.", return_tensors="pt").to(mdl.device)
y = mdl.generate(**x, max_new_tokens=150)
print(tok.decode(y[0], skip_special_tokens=True))

contact: profile: https://huggingface.co/clarkkitchen22
note: Open for collaboration and AI engineering opportunities.
disclaimer: This is an experimental, educational model created on consumer hardware. Outputs may vary or hallucinate — please verify responses for critical tasks.