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Model: QuixiAI/WestLake-7B-v2-laser
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+---
+by David, Fernando and Eric
+
+Sponsored by: [VAGO Solutions](https://vago-solutions.de) and [HyperSpace.Ai](https://hyperspace.computer/)
+
+Join our Discord! https://discord.gg/cognitivecomputations
+
+A laser version of [senseable/WestLake-7B-v2](https://huggingface.co/senseable/WestLake-7B-v2) 
+
+It follows the implementation of laserRMT @ https://github.com/cognitivecomputations/laserRMT
+
+Here, we are controlling layers checking which ones have lower signal to noise ratios (which are more subject to noise), to apply Laser interventions, still using Machenko Pastur to calculate this ratio.
+
+We intend to be the first of a family of experimentations being carried out @ Cognitive Computations.

config.json

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+{
+  "_name_or_path": "senseable/WestLake-7B-v2",
+  "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": "4.37.1",
+  "unsloth_version": "2024.1",
+  "use_cache": true,
+  "vocab_size": 32000
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

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special_tokens_map.json

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tokenizer_config.json

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+{
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+}