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Model: rxavier/Taurus-7B-1.0
Source: Original Platform

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README.md

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+---
+language:
+- en
+license: mit
+tags:
+- chatml
+- mistral
+- instruct
+- openhermes
+- economics
+datasets:
+- rxavier/economicus
+base_model: teknium/OpenHermes-2.5-Mistral-7B
+model-index:
+- name: Taurus-7B-1.0
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 63.57
+      name: normalized accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 83.64
+      name: normalized accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 63.5
+      name: accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 50.21
+    source:
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 78.14
+      name: accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 59.36
+      name: accuracy
+    source:
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=rxavier/Taurus-7B-1.0
+      name: Open LLM Leaderboard
+library_name: transformers
+---
+
+# Taurus 7B 1.0
+
+![image/png](https://i.ibb.co/dGZ50jy/00003-4001299986.png)
+
+## Description
+
+Taurus is an [OpenHermes 2.5](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) finetune using the [Economicus dataset](https://huggingface.co/datasets/rxavier/economicus), an instruct dataset synthetically generated from Economics PhD textbooks.
+
+The model was trained for 2 epochs (QLoRA) using [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl). The exact config I used can be found [here](https://huggingface.co/rxavier/Taurus-1.0-Mistral-7B/tree/main/axolotl).
+
+## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
+Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_rxavier__Taurus-7B-1.0)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |66.40|
+|AI2 Reasoning Challenge (25-Shot)|63.57|
+|HellaSwag (10-Shot)              |83.64|
+|MMLU (5-Shot)                    |63.50|
+|TruthfulQA (0-shot)              |50.21|
+|Winogrande (5-shot)              |78.14|
+|GSM8k (5-shot)                   |59.36|
+
+## Prompt format
+
+Taurus uses **ChatML**.
+
+```
+<|im_start|>system
+System message
+<|im_start|>user
+User message<|im_end|>
+<|im_start|>assistant
+```
+
+## Usage
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
+
+
+model_id = "rxavier/Taurus-7B-1.0"
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16, #torch.float16 for older GPUs
+    device_map="auto", # Requires having accelerate installed, useful in places like Colab with limited VRAM
+)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+generation_config = GenerationConfig(
+                bos_token_id=tokenizer.bos_token_id,
+                eos_token_id=tokenizer.eos_token_id,
+                pad_token_id=tokenizer.pad_token_id,
+            )
+
+system_message = "You are an expert in economics with PhD level knowledge. You are helpful, give thorough and clear explanations, and use equations and formulas where needed."
+prompt = "Give me latex formulas for extended euler equations"
+
+messages = [{"role": "system",
+             "content": system_message},
+            {"role": "user",
+             "content": prompt}]
+tokens = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to("cuda")
+
+with torch.no_grad():
+    outputs = model.generate(inputs=tokens, generation_config=generation_config, max_length=512)
+print(tokenizer.decode(outputs.cpu().tolist()[0]))
+```
+
+## GGUF quants
+
+You can find GGUF quants for llama.cpp [here](https://huggingface.co/rxavier/Taurus-7B-1.0-GGUF).

added_tokens.json

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+{
+  "<|im_end|>": 32000,
+  "<|im_start|>": 32001
+}

axolotl/config.yml

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+base_model: teknium/OpenHermes-2.5-Mistral-7B
+model_type: MistralForCausalLM
+tokenizer_type: LlamaTokenizer
+is_mistral_derived_model: true
+
+datasets:
+  - path: rxavier/economicus
+    type: sharegpt
+    conversation: chatml
+    #shards: 100
+dataset_prepared_path: taurus/train/last_run_prepared
+val_set_size: 0.05
+
+sequence_len: 2048
+sample_packing: true
+pad_to_sequence_len: true
+
+adapter: qlora
+lora_r: 64
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_linear: true
+lora_target_modules:
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+  - gate_proj
+  - down_proj
+  - up_proj
+#lora_modules_to_save:
+#  - embed_tokens
+#  - lm_head
+
+load_in_8bit: false
+load_in_4bit: true
+strict: false
+bf16: true
+fp16: false
+tf32: false
+
+gradient_accumulation_steps: 4
+micro_batch_size: 2
+num_epochs: 2
+optimizer: paged_adamw_8bit
+weight_decay: 0.0
+lr_scheduler: cosine
+learning_rate: 0.0003
+warmup_ratio: 0.03
+adam_beta2: 0.95
+adam_epsilon: 0.00001
+max_grad_norm: 1.0
+
+gradient_checkpointing: true
+early_stopping_patience:
+
+evals_per_epoch: 4
+eval_table_size:
+eval_table_max_new_tokens:
+eval_sample_packing: false
+saves_per_epoch: 4
+debug:
+deepspeed:
+
+fsdp:
+fsdp_config:
+
+train_on_inputs: false
+group_by_length: false
+resume_from_checkpoint:
+
+local_rank:
+logging_steps: 1
+xformers_attention:
+flash_attention: true
+
+output_dir: taurus/train/output
+save_safetensors: true
+
+wandb_project: economicus
+wandb_entity:
+wandb_watch:
+wandb_run_id:
+wandb_log_model:
+
+#special_tokens:
+#  eos_token: "<|im_end|>"
+#tokens:
+#  - "<|im_start|>"
+#  - "<|im_end|>"
+chat_template: chatml

config.json

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+{
+  "_name_or_path": "teknium/OpenHermes-2.5-Mistral-7B",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 32000,
+  "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,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.39.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32002
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 32000,
+  "transformers_version": "4.39.0.dev0"
+}

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special_tokens_map.json

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tokenizer_config.json

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+  "additional_special_tokens": [],
+  "bos_token": "<s>",
+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'You are a helpful assistant.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'<|im_start|>system\n' + system_message + '<|im_end|>\n'}}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "trust_remote_code": false,
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true,
+  "use_fast": true
+}