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Model: lyogavin/Anima-7B-100K
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- llama2
+- 100k
+- 7b
+---
+
+Anima LLM supporting 100K input token length. It's trained based on Llama2 7B, so the license support commercial use!
+
+We carefully curated long QA training dataset from 30k to 100k length to train this model. We also made a lot of memory optimizations to make it scale to 100k tokens.
+
+
+## How to train/infer?
+
+#### install dependencies
+
+```bash
+# Please update the path of `CUDA_HOME`
+export CUDA_HOME=/usr/local/cuda-11.8
+pip install transformers==4.31.0
+pip install sentencepiece
+pip install ninja
+pip install flash-attn --no-build-isolation
+pip install git+https://github.com/HazyResearch/flash-attention.git#subdirectory=csrc/rotary
+pip install git+https://github.com/HazyResearch/flash-attention.git#subdirectory=csrc/xentropy
+pip install evaluate
+pip install git+https://github.com/huggingface/peft.git@v0.4.0
+pip install wandb
+```
+
+#### inference
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+base_model = "lyogavin/Anima-7B-100K"
+tokenizer = AutoTokenizer.from_pretrained(base_model)
+model = AutoModelForCausalLM.from_pretrained(
+            base_model,
+            torch_dtype=torch.float16,
+            trust_remote_code=True,
+            device_map="auto", 
+        )
+model.eval()
+
+prompt = "Where is the capital of US?"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+inputs['input_ids'] = inputs['input_ids'].cuda()
+inputs['attention_mask'] = inputs['attention_mask'].cuda()
+
+# Generate
+generate_ids = model.generate(**inputs, max_new_tokens=30,
+                       only_last_logit=True, # to save memory
+                       use_cache=False, # when run into OOM, enable this can save memory
+                       xentropy=True)
+output = tokenizer.batch_decode(generate_ids, 
+                                skip_special_tokens=True,
+                                clean_up_tokenization_spaces=False)[0]
+
+```
+
+#### Training
+
+```bash
+./run_longer_training.sh
+```
+
+## Evaluations
+
+There's almost none evaluation dataset designed for 100k tokens. So we designed/curated some dataset for this model. We compared this model and several other public/private models.
+
+#### 1. longchat topic retrieval
+
+| Model             | Accuracy     | 
+|-------------------|---------|
+| Claude2 | 0.9    |
+| together llama2 32k        | 0.15 | 
+| longchat 32k 1.5             | 0.05 | 
+| Anima 100K   | 0.5  | 
+
+#### 2. longchat number retrieval
+
+| Model             | Accuracy     | 
+|-------------------|---------|
+| Claude2 | 0.85   |
+| together llama2 32k        | 0.2 | 
+| longchat 32k 1.5             | 0.05 | 
+| Anima 100K   | 0.45 | 
+
+#### 3. Narrative QA in zeroscore
+
+| Model             | F1     | 
+|-------------------|---------|
+| Claude2 | 0.6187   |
+| together llama2 32k        | 0.3833 | 
+| longchat 32k 1.5             | 0.2416 | 
+| Anima 100K   | 0.4919  | 
+
+## Github 
+
+Github repo is [here](https://github.com/lyogavin/Anima/tree/main/anima_100k)

added_tokens.json

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+{
+  "<pad>": 32000
+}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "auto_map": {
+    "AutoModelForCausalLM": "modeling_flash_llama.LlamaForCausalLM"
+  },
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 11008,
+  "max_position_embeddings": 32768,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 32,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "type": "linear"
+  },
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.31.0",
+  "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,
+  "pad_token_id": 0,
+  "transformers_version": "4.31.0"
+}

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