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Model: mrm8488/falcoder-7b
Source: Original Platform

.gitattributes

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README.md

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+---
+tags:
+- generated_from_trainer
+- code
+- coding
+model-index:
+- name: FalCoder
+  results: []
+license: apache-2.0
+language:
+- code
+thumbnail: https://huggingface.co/mrm8488/falcoder-7b/resolve/main/falcoder.png
+datasets:
+- HuggingFaceH4/CodeAlpaca_20K
+pipeline_tag: text-generation
+---
+
+<div style="text-align:center;width:250px;height:250px;">
+    <img src="https://huggingface.co/mrm8488/falcoder-7b/resolve/main/falcoder.png" alt="falcoder logo"">
+</div>
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# FalCoder 🦅👩‍💻
+**Falcon-7b** fine-tuned on the **CodeAlpaca 20k instructions dataset** by using the method **QLoRA** with [PEFT](https://github.com/huggingface/peft) library.
+
+## Model description 🧠
+
+[Falcon 7B](https://huggingface.co/tiiuae/falcon-7b)
+
+
+## Training and evaluation data 📚
+
+[CodeAlpaca_20K](https://huggingface.co/datasets/HuggingFaceH4/CodeAlpaca_20K): contains 20K instruction-following data used for fine-tuning the Code Alpaca model.
+
+
+### Training hyperparameters ⚙
+
+TBA
+
+### Training results 🗒️
+
+| Step | Training Loss | Validation Loss |
+|------|---------------|-----------------|
+| 100  | 0.798500      | 0.767996        |
+| 200  | 0.725900      | 0.749880        |
+| 300  | 0.669100      | 0.748029        |
+| 400  | 0.687300      | 0.742342        |
+| 500  | 0.579900      | 0.736735        |
+
+
+
+### Example of usage 👩‍💻
+```py
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, AutoTokenizer
+
+model_id = "mrm8488/falcoder-7b"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+model = AutoModelForCausalLM.from_pretrained(model_id).to("cuda")
+
+def generate(
+        instruction,
+        max_new_tokens=128,
+        temperature=0.1,
+        top_p=0.75,
+        top_k=40,
+        num_beams=4,
+        **kwargs
+):
+    prompt = instruction + "\n### Solution:\n"
+    print(prompt)
+    inputs = tokenizer(prompt, return_tensors="pt")
+    input_ids = inputs["input_ids"].to("cuda")
+    attention_mask = inputs["attention_mask"].to("cuda")
+    generation_config = GenerationConfig(
+        temperature=temperature,
+        top_p=top_p,
+        top_k=top_k,
+        num_beams=num_beams,
+        **kwargs,
+    )
+    with torch.no_grad():
+        generation_output = model.generate(
+            input_ids=input_ids,
+            attention_mask=attention_mask,
+            generation_config=generation_config,
+            return_dict_in_generate=True,
+            output_scores=True,
+            max_new_tokens=max_new_tokens,
+            early_stopping=True
+        )
+    s = generation_output.sequences[0]
+    output = tokenizer.decode(s)
+    return output.split("### Solution:")[1].lstrip("\n")
+
+instruction = "Design a class for representing a person in Python."
+print(generate(instruction))
+```
+
+### Citation
+```
+@misc {manuel_romero_2023,
+	author       = { {Manuel Romero} },
+	title        = { falcoder-7b (Revision e061237) },
+	year         = 2023,
+	url          = { https://huggingface.co/mrm8488/falcoder-7b },
+	doi          = { 10.57967/hf/0789 },
+	publisher    = { Hugging Face }
+}
+```

config.json

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+{
+  "_name_or_path": "ybelkada/falcon-7b-sharded-bf16",
+  "alibi": false,
+  "apply_residual_connection_post_layernorm": false,
+  "architectures": [
+    "RWForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "auto_map": {
+    "AutoConfig": "tiiuae/falcon-7b--configuration_RW.RWConfig",
+    "AutoModel": "tiiuae/falcon-7b--modelling_RW.RWModel",
+    "AutoModelForCausalLM": "tiiuae/falcon-7b--modelling_RW.RWForCausalLM",
+    "AutoModelForQuestionAnswering": "tiiuae/falcon-7b--modelling_RW.RWForQuestionAnswering",
+    "AutoModelForSequenceClassification": "tiiuae/falcon-7b--modelling_RW.RWForSequenceClassification",
+    "AutoModelForTokenClassification": "tiiuae/falcon-7b--modelling_RW.RWForTokenClassification"
+  },
+  "bias": false,
+  "bos_token_id": 11,
+  "eos_token_id": 11,
+  "hidden_dropout": 0.0,
+  "hidden_size": 4544,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "RefinedWebModel",
+  "multi_query": true,
+  "n_head": 71,
+  "n_layer": 32,
+  "parallel_attn": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.31.0.dev0",
+  "use_cache": true,
+  "vocab_size": 65024
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.31.0.dev0"
+}

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+}

special_tokens_map.json

@@ -0,0 +1,17 @@
+{
+  "additional_special_tokens": [
+    ">>TITLE<<",
+    ">>ABSTRACT<<",
+    ">>INTRODUCTION<<",
+    ">>SUMMARY<<",
+    ">>COMMENT<<",
+    ">>ANSWER<<",
+    ">>QUESTION<<",
+    ">>DOMAIN<<",
+    ">>PREFIX<<",
+    ">>SUFFIX<<",
+    ">>MIDDLE<<"
+  ],
+  "eos_token": "<|endoftext|>",
+  "pad_token": "<|endoftext|>"
+}

tokenizer_config.json

@@ -0,0 +1,7 @@
+{
+  "add_prefix_space": false,
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|endoftext|>",
+  "model_max_length": 2048,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}