初始化项目，由ModelHub XC社区提供模型

Model: pszemraj/perSLIMmon-8b-base
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- persimmon
+---
+
+# perSLIMmon-8b-base
+
+> persimmon-8b went to the vocab lipo clinic 
+
+
+A slimmed-down version of [persimmon-8b-base](https://huggingface.co/adept/persimmon-8b-base) which removes the ~70,000 unused entries in the model vocabulary and tokenizer (see the safetensors layer overview). Should be _slightly_ faster.
+
+Credit: [fine-tune-fuyu](https://github.com/phillip-kravtsov/fine-tune-fuyu) (`scripts/surgery.py` was adapted for persimmon)
+
+
+## inference
+
+install required pkgs:
+
+```sh
+pip install -U transformers accelerate bitsandbytes sentencepiece
+```
+
+load in 4bit & run inference:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+tokenizer = AutoTokenizer.from_pretrained("pszemraj/perSLIMmon-8b-base")
+model = AutoModelForCausalLM.from_pretrained(
+    "pszemraj/perSLIMmon-8b-base",
+    load_in_4bit=True, # GPU required
+    torch_dtype="auto",
+    device_map="auto",
+)
+inputs = tokenizer("The weather is always wonderful", return_tensors="pt").to(
+    model.device
+)
+tokens = model.generate(
+    **inputs,
+    max_new_tokens=64,
+    temperature=0.75,
+    top_p=0.95,
+    epsilon_cutoff=1e-5,
+    repetition_penalty=1.05,
+    renormalize_logits=True,
+    do_sample=True,
+) # adapt inference params as needed
+
+print(tokenizer.decode(tokens[0], skip_special_tokens=True))
+```
+
+inference is decently fast on a colab T4:
+
+```
+CPU times: user 6.01 s, sys: 138 ms, total: 6.15 s
+Wall time: 6.23 s
+```

config.json

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+{
+  "_name_or_path": "/content/perSLIMmon-8b",
+  "architectures": [
+    "PersimmonForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 71013,
+  "eos_token_id": 71013,
+  "hidden_act": "relu2",
+  "hidden_dropout": 0.6,
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 16384,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 16384,
+  "model_type": "persimmon",
+  "num_attention_heads": 64,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 64,
+  "partial_rotary_factor": 0.5,
+  "pretraining_tp": 1,
+  "qk_layernorm": true,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 25000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.36.0.dev0",
+  "use_cache": true,
+  "vocab_size": 192144
+}

generation_config.json

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+  "_from_model_config": true,
+  "bos_token_id": 71013,
+  "eos_token_id": 71013,
+  "transformers_version": "4.36.0.dev0"
+}

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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