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README.md

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+---
+license: other
+license_name: yi-34b
+license_link: https://huggingface.co/01-ai/Yi-34B-200K/blob/main/LICENSE
+---
+
+
+# Tess-2.0-Yi-34B-200K
+Tess, short for Tesoro (Treasure in Italian), is a general purpose Large Language Model series. Tess-2.0-Yi-34B-200K was trained on the 01-ai/Yi-34B-200K base.
+
+# Prompt Format:
+
+```
+SYSTEM: <ANY SYSTEM CONTEXT>
+USER: 
+ASSISTANT: 
+```
+
+<br>
+
+![Tesoro](https://huggingface.co/migtissera/Tess-7B-v2.0/resolve/main/Tesoro.png)
+
+<br>
+
+### Below shows a code example on how to use this model:
+
+```python
+import torch, json
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_path = "migtissera/Tess-2.0-Yi-34B-200K"
+output_file_path = "./conversations.jsonl"
+
+model = AutoModelForCausalLM.from_pretrained(
+    model_path,
+    torch_dtype=torch.float16,
+    device_map="auto",
+    load_in_8bit=False,
+    trust_remote_code=True,
+)
+
+tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+
+
+def generate_text(instruction):
+    tokens = tokenizer.encode(instruction)
+    tokens = torch.LongTensor(tokens).unsqueeze(0)
+    tokens = tokens.to("cuda")
+
+    instance = {
+        "input_ids": tokens,
+        "top_p": 1.0,
+        "temperature": 0.5,
+        "generate_len": 1024,
+        "top_k": 50,
+    }
+
+    length = len(tokens[0])
+    with torch.no_grad():
+        rest = model.generate(
+            input_ids=tokens,
+            max_length=length + instance["generate_len"],
+            use_cache=True,
+            do_sample=True,
+            top_p=instance["top_p"],
+            temperature=instance["temperature"],
+            top_k=instance["top_k"],
+            num_return_sequences=1,
+        )
+    output = rest[0][length:]
+    string = tokenizer.decode(output, skip_special_tokens=True)
+    answer = string.split("USER:")[0].strip()
+    return f"{answer}"
+
+
+conversation = f"SYSTEM: Answer the question thoughtfully and intelligently. Always answer without hesitation."
+
+
+while True:
+    user_input = input("You: ")
+    llm_prompt = f"{conversation} \nUSER: {user_input} \nASSISTANT: "
+    answer = generate_text(llm_prompt)
+    print(answer)
+    conversation = f"{llm_prompt}{answer}"
+    json_data = {"prompt": user_input, "answer": answer}
+
+    ## Save your conversation
+    with open(output_file_path, "a") as output_file:
+        output_file.write(json.dumps(json_data) + "\n")
+
+```
+
+<br>
+
+#### Limitations & Biases:
+
+While this model aims for accuracy, it can occasionally produce inaccurate or misleading results. 
+
+Despite diligent efforts in refining the pretraining data, there remains a possibility for the generation of inappropriate, biased, or offensive content. 
+
+Exercise caution and cross-check information when necessary. This is an uncensored model.
+
+
+<br>

added_tokens.json

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+{
+  "</s>": 64001,
+  "<s>": 64000
+}

config.json

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+{
+    "_name_or_path": "/home/migel/Tess-2-Yi-qlora/merged",
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 64000,
+    "eos_token_id": 64001,
+    "hidden_act": "silu",
+    "hidden_size": 7168,
+    "initializer_range": 0.02,
+    "intermediate_size": 20480,
+    "max_position_embeddings": 200000,
+    "model_type": "llama",
+    "num_attention_heads": 56,
+    "num_hidden_layers": 60,
+    "num_key_value_heads": 8,
+    "pad_token_id": 0,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": null,
+    "rope_theta": 10000000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "float16",
+    "transformers_version": "4.36.2",
+    "use_cache": false,
+    "vocab_size": 64002,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.16",
+        "bits": 6.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "pad_token_id": 0,
+  "transformers_version": "4.36.2"
+}

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