commit 1caced4520ca4c6b618079798369871c77a3cd4f Author: ModelHub XC Date: Wed Jun 17 16:26:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: duyntnet/Azzurro-imatrix-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..07c341c --- /dev/null +++ b/.gitattributes @@ -0,0 +1,62 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text 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+device = "cpu" # if you want to use the gpu make sure to have cuda toolkit installed and change this to "cuda" + +model = AutoModelForCausalLM.from_pretrained("MoxoffSpA/Azzurro") +tokenizer = AutoTokenizer.from_pretrained("MoxoffSpA/Azzurro") + +question = """Quanto è alta la torre di Pisa?""" +context = """ +La Torre di Pisa è un campanile del XII secolo, famoso per la sua inclinazione. Alta circa 56 metri. +""" + +prompt = f"Domanda: {question}, contesto: {context}" + +messages = [ + {"role": "user", "content": prompt} +] + +encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt") + +model_inputs = encodeds.to(device) +model.to(device) + +generated_ids = model.generate( + model_inputs, # The input to the model + max_new_tokens=128, # Limiting the maximum number of new tokens generated + do_sample=True, # Enabling sampling to introduce randomness in the generation + temperature=0.1, # Setting temperature to control the randomness, lower values make it more deterministic + top_p=0.95, # Using nucleus sampling with top-p filtering for more coherent generation + eos_token_id=tokenizer.eos_token_id # Specifying the token that indicates the end of a sequence +) + +decoded_output = tokenizer.decode(generated_ids[0], skip_special_tokens=True) +trimmed_output = decoded_output.strip() +print(trimmed_output) +``` \ No newline at end of file