初始化项目，由ModelHub XC社区提供模型

Model: liminerity/Mistral-quiet-star-demo
Source: Original Platform

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README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- mistral
+- trl
+base_model: unsloth/mistral-7b-bnb-4bit
+datasets:
+- gate369/Alpaca-Star
+---
+- QSTAR
+-  I think this model is proof of my theory that you dont need a special architecture to train a llm to reason. The techniques i imployed to make this could 
+   be greatly expanded on and coupled with a agent system to achieve a functioning low cost agi system.
+
+- Steps:        -Loss:
+- 1	          - 1.373000
+- 2	          - 1.551400
+- 3	          - 1.083100
+- 4	          - 1.164900
+- 5 	      - 1.196500
+- 6	          - 1.015400
+-       ....
+- 363	     - 0.019000
+- 364	     - 0.017600
+- 365	     - 0.015600
+- 366	     - 0.016700
+- 367	     - 0.016400
+- 368	     - 0.016600
+- 369	     - 0.017600
+- heres a conversation i had with the model:
+- user: "hi there. id like to build a time machine. how might i go about achieving this?"
+- assistant: "|startthought| To build a time machine, I need to figure out how to move through time just like we move through space. That means finding a way to change my 
+          frame of reference from the stationary Earth to one that's moving forward in time. |endthought| One approach is to use Einstein's theory of relativity and massive 
+          objects with strong gravitational fields, like black holes or neutron stars. By warping spacetime, these objects can slow down time for an observer passing by. 
+          Another idea is to explore quantum mechanics and the notion of entanglement between particles. If I could create a pair of entangled particles and keep one, the 
+          other might appear elsewhere in space-time, effectively teleporting it through time. Yet another approach is to look at cosmic rays and high-energy particle 
+          collisions, which can create short-lived particles that seem to violate the forward-in-time direction of time. Understanding these phenomena might lead to a 
+          way to control time flow. Ultimately, building a functional time machine will require advancing our understanding of these fundamental physical principles and 
+          finding a way to apply them technologically. It's a grand challenge that has captivated scientists and science fiction writers alike for centuries."
+- user: "how might we make use of this phenomena to create a functioning time machine?"
+- assistant: "|startthought| To make use of these phenomenas to create a funcitoning time machine, we need to find a way to control and harness them technologically. 
+          That could mean developing advanced gravitational lensing techniques to manipulate space-time around massive objects, exploring quantum entanglement 
+          in more complex systems, or finding a way to generate the high-energy particle collision conditions needed to create tachyons. It's likely that we'll need to 
+          understand and combine multiple approaches to make a functional time machine a reality. |endthought| One approach might be to focus on developing advanced 
+          gravitational lensing techniques. This could allow us to control the warping of space-time around massive objects like black holes or neutrino stars, creating 
+          stable time vortexes that we can pass through. Another idea is to explore quantum entanglement in more complex systems. If we could create and maintain a 
+          large-scale entangled state between two particles, we might be able to use one particle as a clock while the other appears elsewhere in space-time, effectively 
+          teleporting it through time. Yet another approach is to look at high-energy particle collision phenomenas like those created in large hadron colliders or 
+          supernova explosions. These events can generate short-lived particles called tachyons, which seem to move faster than the speed of light and violate the 
+          forward-in-time direction of time. If we could understand and control this phenomena, we might be able to create a stable source of tachyons that could be 
+          used to power a time machine. Ultimately, making a functional time machine will require advancing our understanding of these fundamental physical principles 
+          and finding a way to apply them technologically. It's a grand challenge that has captivaed scientists and science fiction writers alike for centuries."
+
+
+
+- the data set will need more work but this shows insane potential
+# Uploaded  model
+
+- **Developed by:** liminerity
+- **License:** apache-2.0
+- **Finetuned from model :** unsloth/mistral-7b-bnb-4bit
+This model was trained on a alpaca based dataset i made using perplexity and claude 3. The dataset is meant to encourage the llm the think before speaking
+This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

config.json

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+{
+  "_name_or_path": "unsloth/mistral-7b-bnb-4bit",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.38.2",
+  "unsloth_version": "2024.3",
+  "use_cache": true,
+  "vocab_size": 32000
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.38.2"
+}

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+    "model.layers.8.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
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+    "model.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
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+    "model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
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+    "model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
+    "model.norm.weight": "pytorch_model-00003-of-00003.bin"
+  }
+}

special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

@@ -0,0 +1,43 @@
+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 32768,
+  "pad_token": "<unk>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}