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Model: duyhv1411/Llama-3.2-1B-en-vi
Source: Original Platform

README.md

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+---
+language:
+- en
+- vi
+library_name: transformers
+tags:
+- chat
+- llama
+- finetune
+- peft
+base_model: duyhv1411/Llama-3.2-1B-en-vi
+model_name: Llama-3.2-1B-en-vi
+pipeline_tag: text-generation
+inference: false
+---
+
+# duyhv1411/Llama-3.2-1B-en-vi
+
+This model is an advanced iteration of the powerful `meta-llama/Llama-3.2-1B-Instruct`, specifically fine-tuned to enhance its capabilities in generic domains.
+
+# How to use
+
+```python
+
+# Use a pipeline as a high-level helper
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+merged_model = AutoModelForCausalLM.from_pretrained("duyhv1411/Llama-3.2-1B-en-vi",
+        device_map="auto",
+        trust_remote_code=True,)
+tokenizer = AutoTokenizer.from_pretrained("duyhv1411/Llama-3.2-1B-en-vi")
+
+chat = [{"role": "user", "content": "Cách tính lương gross?"}]
+
+tokenized_chat = tokenizer.encode(tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True), return_tensors="pt").to(torch.device("cuda"))
+
+outputs = merged_model.generate(tokenized_chat, max_new_tokens=1024, do_sample=True, temperature = 0.9) 
+print(tokenizer.decode(outputs[0][len(tokenized_chat[0]):]))
+
+
+from transformers import pipeline
+
+chat = [{"role": "user", "content": "Cách tính lương gross?"}]
+prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
+
+pipe = pipeline(task="text-generation", model=merged_model, tokenizer=tokenizer, device_map="auto", return_full_text=False)
+print(pipe(prompt, max_new_tokens=1024, do_sample=True, temperature=0.9)[0]["generated_text"])
+```