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Uzaib52
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Model Details
Model Provider
Uzaib52
Model Tree
unsloth/llama-3-8b-Instruct-bnb-4bit
Input Modalities
Output Modalities
Supported Functionality
unsloth/llama-3-8b-Instruct-bnb-4bitIf you want to chat with this model, open a new Google Colab notebook, make sure to change the runtime to T4 GPU (Runtime > Change runtime type > T4 GPU), and run the following code:
python
# 1. DEPENDENCY INSTALLATIONimport sysimport subprocess print("Installing Unsloth (Fast-Track Mode)... Please wait ~30-40 seconds.") # install optimized wheels for Colab to prevent import subprocess.run([sys.executable, "-m", "pip", "install", "--quiet", "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git", "xformers", "trl", "peft", "transformers", "accelerate", "bitsandbytes"]) import siteimport importlibimportlib.invalidate_caches()site.main() print("Installation complete! Loading UCortex Model...") # 2. QUICK LOAD THE MODELtry: from unsloth import FastLanguageModelexcept ModuleNotFoundError: import os sys.path.append('/usr/local/lib/python3.12/dist-packages') from unsloth import FastLanguageModel import torchfrom transformers import TextIteratorStreamerfrom threading import Thread model_name = "Uzaib52/ucortex-llama3-8b"max_seq_length = 2048 model, tokenizer = FastLanguageModel.from_pretrained( model_name = model_name, max_seq_length = max_seq_length, load_in_4bit = True, device_map = "cuda")FastLanguageModel.for_inference(model)print("UCortex Chatbot is active! Type 'exit' to stop.\n" + "="*50) # 3. DIRECT CONVERSATION LOOPprompt_format = "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" while True: user_input = input("\n You: ") if user_input.lower() in ["exit", "quit"]: print(" UCortex: Bye!") break if not user_input.strip(): continue formatted_prompt = prompt_format.format(user_input) inputs = tokenizer([formatted_prompt], return_tensors="pt").to("cuda") streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=512, use_cache=True) thread = Thread(target=model.generate, kwargs=generation_kwargs) thread.start() print("UCortex: ", end="", flush=True) for new_text in streamer: print(new_text, end="", flush=True) print()# 1. DEPENDENCY INSTALLATIONimport sysimport subprocess print("Installing Unsloth (Fast-Track Mode)... Please wait ~30-40 seconds.") # install optimized wheels for Colab to prevent import subprocess.run([sys.executable, "-m", "pip", "install", "--quiet", "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git", "xformers", "trl", "peft", "transformers", "accelerate", "bitsandbytes"]) import siteimport importlibimportlib.invalidate_caches()site.main() print("Installation complete! Loading UCortex Model...") # 2. QUICK LOAD THE MODELtry: from unsloth import FastLanguageModelexcept ModuleNotFoundError: import os sys.path.append('/usr/local/lib/python3.12/dist-packages') from unsloth import FastLanguageModel import torchfrom transformers import TextIteratorStreamerfrom threading import Thread model_name = "Uzaib52/ucortex-llama3-8b"max_seq_length = 2048 model, tokenizer = FastLanguageModel.from_pretrained( model_name = model_name, max_seq_length = max_seq_length, load_in_4bit = True, device_map = "cuda")FastLanguageModel.for_inference(model)print("UCortex Chatbot is active! Type 'exit' to stop.\n" + "="*50) # 3. DIRECT CONVERSATION LOOPprompt_format = "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" while True: user_input = input("\n You: ") if user_input.lower() in ["exit", "quit"]: print(" UCortex: Bye!") break if not user_input.strip(): continue formatted_prompt = prompt_format.format(user_input) inputs = tokenizer([formatted_prompt], return_tensors="pt").to("cuda") streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) generation_kwargs = dict(inputs, streamer=streamer, max_new_tokens=512, use_cache=True) thread = Thread(target=model.generate, kwargs=generation_kwargs) thread.start() print("UCortex: ", end="", flush=True) for new_text in streamer: print(new_text, end="", flush=True) print()