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Model: Achiraf01/mistral-immigration-canada-final
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
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+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
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+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
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+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
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+[More Information Needed]
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+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+#### Metrics
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+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
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+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
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+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
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+#### Hardware
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+
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+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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+**BibTeX:**
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+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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+## Model Card Contact
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config.json

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+{
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "float16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "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": null,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.3.0",
+  "use_cache": true,
+  "vocab_size": 32768
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "5.3.0"
+}

handler.py

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+# handler.py
+from typing import Any, Dict
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+
+class EndpointHandler:
+    def __init__(self, path: str = ""):
+        # Quantization 8-bit → réduit ~14 GB à ~7 GB VRAM
+        bnb_config = BitsAndBytesConfig(
+            load_in_8bit=True,
+        )
+
+        self.tokenizer = AutoTokenizer.from_pretrained(path)
+        self.tokenizer.pad_token = self.tokenizer.eos_token
+
+        self.model = AutoModelForCausalLM.from_pretrained(
+            path,
+            quantization_config=bnb_config,
+            device_map="auto",
+            torch_dtype=torch.float16,
+        )
+        self.model.eval()
+
+    def __call__(self, data: Dict[str, Any]) -> Any:
+        inputs = data.get("inputs", "")
+        parameters = data.get("parameters", {})
+
+        max_new_tokens = parameters.get("max_new_tokens", 512)
+        temperature    = parameters.get("temperature", 0.3)
+        repetition_penalty = parameters.get("repetition_penalty", 1.1)
+        return_full_text   = parameters.get("return_full_text", False)
+
+        tokenized = self.tokenizer(
+            inputs,
+            return_tensors="pt",
+            padding=True,
+            truncation=True,
+            max_length=2048,
+        ).to("cuda")
+
+        # ✅ FIX : Mistral n'utilise pas token_type_ids
+        tokenized.pop("token_type_ids", None)
+
+        with torch.no_grad():
+            output_ids = self.model.generate(
+                **tokenized,
+                max_new_tokens=max_new_tokens,
+                temperature=temperature,
+                repetition_penalty=repetition_penalty,
+                do_sample=True,
+                pad_token_id=self.tokenizer.eos_token_id,
+            )
+
+        # Retirer le prompt si return_full_text=False
+        if not return_full_text:
+            input_len = tokenized["input_ids"].shape[1]
+            output_ids = output_ids[:, input_len:]
+
+        generated = self.tokenizer.decode(
+            output_ids[0],
+            skip_special_tokens=True,
+        )
+
+        return [{"generated_text": generated}]

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:24c76f1678f8ea69c47991c970aef43f3722d3a5053c9c19ab3b24d78a071447
+size 14496080848

requirements.txt

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+bitsandbytes>=0.43.0
+accelerate>=0.27.0

tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "tokenizer_backend": "tokenizers",
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "is_local": false,
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": null,
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}